Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.

Who you are

We are looking for a highly motivated and analytical Data Scientist to join our growing data team. You will play a key role in extracting insights from large datasets, building predictive models, and supporting data-driven decision-making across departments.

What you'll do

• Collect, process, and analyze large datasets from multiple sources
• Build and deploy machine learning models to solve business problems
• Design and implement A/B tests and statistical analyses
• Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements
• Communicate complex data insights in a clear and actionable manner to stakeholders
• Develop dashboards and visualizations to monitor key metrics
• Stay current with the latest trends and technologies in data science and AI

What we're looking for

• Bachelor’s and or Master’s degree in Computer Science, Mathematics, Statistics, or related field
• 4+ years of proven experience as a Data Scientist or Data Analyst
• Strong knowledge of Python/R and SQL
• Hands-on experience with machine learning frameworks (e.g., scikit learn, tensroflow, pytorch)
• Experience with big data tools (e.g., Spark, Hadoop)
• Familiarity with data visualization tools
• Strong analytical, problem-solving, and communication skills

While not required, these are a plus:

• Experience with cloud platforms preferably AWS (S3, Sagemaker, Airflow etc)
• Strong SQL skills, with experience in Snowflake, MySQL, and PostgreSQL
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker)

3 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite

About Zuora

At Zuora, we help businesses grow smarter and adapt faster. Our platform powers modern business models — from subscriptions and usage-based pricing to AI-driven and outcome-based offerings — helping companies launch new products, automate complex billing, and unlock predictable, recurring revenue.

We’ve led the Subscription Economy for more than a decade. Now we’re evolving again by building the definitive platform for quote to cash and helping companies monetize their products and services with an adaptable, AI-ready foundation.

The Opportunity

We’re looking for a strong technical contributor to drive AI/ML innovation and deliver real business impact through intelligent solutions.

You’ll:

• Identify high-impact opportunities using AI/ML to solve customer and business problems
• Partner with stakeholders and influence decisions through data-driven insights
• Build and deploy end-to-end ML models (including LLMs) using structured and unstructured data
• Collaborate with engineering teams to develop scalable data and ML pipelines
• Take full ownership from idea to production, delivering measurable business outcomes

This role is ideal for someone who can combine deep technical expertise with business thinking to simplify complexity and build impactful, production-ready AI solutions.

About You

1. 7+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience
2. Curious mind to learn, explore and identify biggest customer opportunities
3. Build strong relationships across both technical and business/product teams, earn trust with leadership
4. Driven towards forming opinions and conclusions through data and experimentation, rather than anecdotes and hearsay
5. Willingness to dive deep into the tech stack as well as hands-on coding
6. Experience in building end to end ML models, across the ML lifecycle
7. Strong communication and leadership presence
8. Technical skills- hands on with scripting required, with knowledge or willingness to learn tools/softwares. Knowledge of R, SQL, Python, Statistical modeling, experience with AWS/Azure/GCP ML suite
9. Experience in the following domains/industries preferred- SaaS, ecommerce, pricing or payments
10. Bachelors/Masters in a technical or natural sciences domain from a top university

Even if you feel like you meet some, but not all of the qualifications, we would love it if you take the time to apply to the role. As we evolve and scale up a relatively new team, we strongly believe that a diverse team structure will accelerate progress towards our objectives.

The Team

Zuora Platform Tech is at the forefront of technological and business transformation, tackling complex, ambiguous problems to drive innovation. As part of the AIMS team (AI, ML, and Science), you’ll work on applying advanced AI and data science to enable total monetization across Zuora’s product suite and beyond.

The team operates at the intersection of AI, business strategy, and product innovation, solving high-impact problems like pricing, forecasting, segmentation, and optimization. The tech stack includes Java, Spring, Microservices, Kafka, Spark, NodeJS, AWS, Kubernetes, Terraform, and AngularJS.

Benefits

Zuora offers a comprehensive total rewards package designed to support ZEOs’ wellbeing, growth, and flexibility. While specific offerings may vary by country, we typically provide:

• Competitive compensation, variable bonus and performance-based reward opportunities, and retirement programs
• Medical, dental, and vision insurance
• Generous, flexible time off, plus paid holidays, wellness days, and a company-wide year-end break
• Paid parental leave (including fully paid leave for eligible ZEOs, subject to local policy)
• Learning & development stipend to support ongoing growth
• Opportunities to volunteer and give back, including charitable donation matching where available
• Mental wellbeing resources and support

*Benefits may vary by location; details will be shared during the interview process

#ZEOLife at Zuora

ZEOs (our employees) are empowered to take ownership, challenge the status quo, and make a real impact. We:

• Collaborate deeply across teams and regions
• Learn constantly and iterate often
• Build an inclusive, high-performance culture where people feel inspired, connected, and valued

Our Commitment to an Inclusive Workplace

Think, be and do you.
At Zuora, different perspectives, experiences, and contributions matter — everyone counts.

Zuora is proud to be an Equal Opportunity Employer committed to creating an inclusive environment for all. We do not discriminate on the basis of, and consider individuals seeking employment with Zuora without regard to, race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance@zuora.com (or local equivalent, where applicable).

Smartsheet is seeking a Senior Data Scientist to drive growth and customer retention through Applied AI and advanced analytics. With thousands of subscribing organizations and millions of users, you will have the opportunity to make a meaningful impact by leveraging data science to drive Sales, Customer Success, and Monetization strategies. You are curious, have strong data science and machine learning skills and the ability to communicate key insights effectively. You will work primarily with Go to Market Teams and will be a part of Smartsheet's Data Science & Business Intelligence team.

You Will:

• Partner with Sales and Customer Success teams, understand their goals, and execute on opportunities to draw relevant insights and drive tangible impact
• Develop and implement machine learning based Cross-sell/Upsell models and Product Recommender models to drive Sales & Monetization
• Build and deploy predictive models for Customer Churn and identify proactive churn risk prediction signals to drive retention
• Drive the full analytics lifecycle from understanding the business objective, analyzing the data to developing automated reporting and visualizations
• Collaborate with cross-functional teams to integrate data science solutions into business processes
• Effectively present analysis to both technical and non-technical audiences and give data-based recommendations to encourage data-driven decisions 
• Drive a data culture within the Go To Market  teams

You Have:

• Bachelor's degree and 8+ years of experience (or 10+ years of experience)
• Extensive knowledge and practical experience in several of the following areas: Applied AI, machine learning, statistics, propensity modeling, churn prediction and recommender systems
• Proficient analytical skills for problem solving; can perform descriptive analysis, diagnostic analysis, predictive analysis and prescriptive analysis.
• Strong programming skills in Python or R
• Proficient in SQL and skilled in visualization tools (ex. Tableau)
• Strong track record of forming effective cross-functional partnerships
• Experience using data to meaningfully impact Sales & Customer Success strategy execution
• Experience communicating analysis clearly to others
• Ability to research and learn new technologies, tools, and methodologies
• Ability to thrive in a dynamic environment, find opportunities and execute in both independent and collaborative environments
• As a senior member of the data science team help mentor and help grow members of the team

Scopely is looking for a Data Analyst to join Bingo Bash team in Bangalore on a hybrid basis!

At Scopely, we care deeply about what we do and want to inspire play, every day - whether in our work environments alongside our talented colleagues, or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people around the world daily. 

Bingo Bash is a highly international team working on the biggest video game from India to date (measured by revenue).  Here you will work on a top-grossing F2P game with significant and growing daily revenues, and help create fresh content for our players..

What You’ll Do 

• Work collaboratively with game teams to deliver actionable insights into our games to further increase user acquisition, engagement and monetization using statistical techniques & provide reports
• Design and implement new analytics events and queries for new game features, game events and player offers, to make sure the team gets the information they need to evaluate and improve the game
• Proactively perform a wide range of analyses to identify/analyze/interpret trends, issues, and opportunities across games and perform competitor analysis
• Answer business-related questions & generate business reports through exploratory data analyses and ad-hoc reporting
• Design and implement advanced statistical testing for specific problem-solving needs(e.g. A/B testing)

What We’re Looking For 

• B.Tech/BS in Computer Science, Statistics, Math, Physics or other quantitative disciplines
• 2+ years of overall experience in a data analyst, financial analyst, scientist or similar role performing quantitative, statistical or financial analysis
• 2+ years’ experience using SQL/Python, including complex queries from multiple data sources
• 2+ years’ experience creating reports using Tableau/Looker or a similar reporting system
• Experience creating, operating and analyzing multiple simultaneous A/B tests
• Excellent analytical and problem-solving skills, including forecasting and performance marketing analysis
• Strong communication and presentation skills, including extensive use of chart and table tools
• Passion for speed and large data sets

Bonus Points 

• Demonstrates openness to using AI-enabled tools to improve analytical workflows, accelerate insight generation, and support high-quality data-driven decision-making.
• Advanced degrees a plus
• 2+ years within the mobile gaming domain
• Strong statistical background
• Experience with R, SAS, SPSS, Matlab or other statistical modeling packages
• Had experience of onboarding/early funnel analysis 

At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that!   We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employmentopportunities and welcome individuals from all backgrounds to join us & embrace the Adventure!

Location Details: Gurugram

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​

This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team.

Join our Team

If you are passionate about machine learning and want to make a difference for millions of small businesses, join our DnAI (Data and Artificial Intelligence) team at GoDaddy as a Senior Machine Learning Scientist. You will have the opportunity to build cutting-edge machine learning models and Generative AI solutions to build intelligent software that delight our customers. You will work with highly skilled engineers in building comprehensive solutions to challenging business problems in customer experience, personalization; as well as solve technical problems in model evaluation, simulation and more.

What you'll get to do...

• Develop and implement advanced machine learning algorithms. 
• Build Intelligent Software using Large Language Models (AI Agents). 
• Design and refine ML models to enhance their performance, scalability, and robustness. 
• Assess, design and curate comprehensive evaluations for open-ended GenerativeAI problems. 
• Collaborate with cross-functional teams to integrate ML solutions within broader product and platform initiatives. 
• Drive the exploration and adoption of cutting-edge ML technologies to maintain our competitive edge in the industry. 

Your experience should include...

• 6+ years of overall experience in machine learning related roles.
• Strong knowledge of machine learning algorithms, tools, and techniques, such as supervised and unsupervised learning, deep learning, computer vision, natural language processing, etc. 
• Familiarity with AI assisted coding tools like Cursor, Claude Code or VS Code. 
• Proficient in Python programming language with familiarity with software engineering best practices, such as version control, code review, CI/CD, etc. 
• Proficiency with prompt engineering and large language models (LLM) and Natural Language Processing (NLP).

You might also have...

• Experience building conversational systems. 
• Experience in designing comprehensive evaluations and verification methods. 
• Proficiency in Typescript is a plus.

We've got your back...  We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy’s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way. 

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us...  GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us. 

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com. 

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

The Role

Lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

The Role

The Senior Data Scientist will lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

ABOUT THE TEAM

Anduril’s Tactical Recon & Strike (TRS) is a division with two missions: 1) build highly capable autonomous drones, and 2) build solid rocket motors at scale. We transform products like Ghost, Anvil, Bolt, and Altius from early concepts into fully operational capabilities by partnering closely with specialist engineering, operations, and production teams. Through our Anduril Rocket Motor Systems (RMS) team, we design and manufacture solid rocket motors using advanced materials, proprietary formulations, and high-volume production methods—delivering safe, reliable propulsion systems that support a wide range of mission requirements. TRS hires software engineers & hardware engineers, who are excited to build across a diverse and powerful portfolio—from autonomous aerial systems to high-performance solid rocket motors. Our teams contribute to highly capable autonomous robotics systems and propulsion products that operate reliably in the most demanding mission environment.

ABOUT THE JOB

As Senior Scientist, you will support the development of Anduril’s proprietary metal-powder fuel formulation through chemical and materials research and development. The right person for this role has hands-on skills in chemical and materials research and development and also in project management. If you are someone who is detail oriented and passionate about turning laboratory development into next-generation, real-world capabilities this role is for you.

WHAT YOU’LL DO

• Conduct experimental research under the guidance of a senior principal scientist.
• Collaborate with a multi-specialized team.
• Analyze data & plan experiments & make brief technical presentations.
• Support multi-threaded project management.

REQUIRED QUALIFICATIONS

• Master’s degree in chemical, materials science, or metallurgical engineering, chemistry, or related fields.
• Experience with air-sensitive chemistries, materials and techniques.
• Fundamental knowledge of material and chemical sciences.
• Experience in team-oriented project execution.
• Eligible to obtain and hold a U.S. Top Secret Security Clearance.

PREFERRED QUALIFICATIONS

• Ph. D degree in chemical, materials science, or metallurgical engineering, chemistry, or related fields.
• A preference for inorganic chemistry, metallurgical engineering, or material science.
• Experience with reactive metals
• Experience with surface chemistry.
• Experience with team project leadership & management. Well-developed soft skills for technical project collaboration.
• Experience with materials characterization techniques and interpretation (ICP, gravimetric analysis, microscopy, DSC, spectrometry, etc.).
• Experience with propellant or energetic materials.

About HG Insights

HG Insights is the pioneer of Revenue Growth Intelligence. For more than a decade, we have delivered comprehensive, AI-driven datasets on B2B buyers, technology adoption, IT spend, and buyer intent, sourced from billions of data points. Today, we are a trusted partner to Fortune 500 technology companies, hyperscalers, and innovative B2B vendors seeking precise go-to-market analytics and decision-making.

Through an evolving suite of AI agents that incorporate first-party data and buyer signals, HG Insights enables AI-powered GTM automation across sales, marketing, RevOps, and data analytics teams, modernizing GTM execution from strategy through activation.

Role Overview

The Applied Data Scientist - Research is a collaborative analytical partner to the Head of Data Science, contributing to the design and validation of GTM insights that power the Contextual Intelligence initiative.

You will co-develop insight logic, selecting signals, designing scoring frameworks, prototyping models in Python, and validating outputs. You will also contribute to the production-ready briefs that are implemented in the data production pipeline by the engineering team.

This role sits at the intersection of statistical modeling, structured data analysis, and applied AI. You are comfortable reasoning about how to measure something rigorously, how entities and relationships in a knowledge graph can be leveraged, and how to use LLMs as a practical tool in the insight development workflow, not as a subject of research, but as part of the toolkit.

What You Will Do

Insight & Model Development

• Co-develop scoring frameworks and metrics models, contributing to signal selection, weighting logic, and model structure across a range of GTM insight types (acquisition,expansion, retention, strategic)
• Prototype insight logic in Python notebooks: assembling features from HG's structured data assets, implementing model components, and stress-testing outputs.
• Design and run validation experiments to confirm that insight outputs are directionally correct, well-calibrated, and meaningful across the full vendor universe
• Contribute to ontology and entity design, thinking through how vendors, products, companies, and relationships should be structured to support a given insight, informed by a conceptual understanding of the knowledge graph schema

Production Brief Development

• Translate insight designs into clear, implementation-ready production briefs 
• Document model specifications precisely: component definitions, feature engineering, aggregation logic, edge case handling, and expected output distributions
• Participate in handoff reviews with the production function, answering implementation questions and refining specs based on feasibility feedback

Insight Research & Discovery

• Contribute to the prioritized insights catalog, researching new insight ideas, assessing data availability, and framing feasibility
• Stay current on GTM data science approaches, competitive intelligence methodologies, and relevant analytical techniques that could expand the insight library

What We're Looking For

Core Skills

• Statistical modeling depth: Ability to design and implement a range of scoring and metrics models from first principles; comfortable with component weighting, normalization, signed rate-of-change metrics, composite aggregation, and distribution analysis; knows when a technique is appropriate and why 
• Python for analytical prototyping: Strong notebook-based Python for data manipulation, feature construction, model prototyping, and output validation; pandas, NumPy, and Scikit are daily 
• SQL: Proficient in querying structured data at scale; used for signal extraction, feature derivation, and validation checks across large vendor and company datasets
• Analytical rigor & validation thinking: Ability to critically evaluate whether a model is measuring what it claims to measure; designs validation experiments, checks edge cases, and flags when outputs don't pass a sanity check
• Clear technical communication: Able to translate analytical logic into precise written specifications; the production brief is a key deliverable 

Applied AI & Graph Literacy

• LLM API usage: Hands-on experience using Claude, GPT, or equivalent APIs as a practical tool; can design effective prompts, integrate LLM steps into an analytical workflow, and evaluate output quality critically
• Knowledge graph concepts: Conceptual understanding of how entities, relationships, and properties are structured in a graph; able to reason about how graph-derived features (e.g., vendor-product-company traversals) should inform insight design, without necessarily writing production Cypher 

Nice to Have

• GTM/Management Consulting, or IT Research experience, familiarity with concepts like install base, intent signals, competitive intelligence, and market analysis. Experience writing Cypher or querying graph-structured data directly
• Experience working collaboratively with engineering, product and GTM teams
• Experience in a B2B SaaS or data products environment

Tools & Environment

Primary

• Python (pandas, NumPy, scipy, Jupyter)
• SQL
• LLM APIs (Claude, GPT)
• Git and version control

Working Knowledge

• Databricks
• Cloud storage 
• Knowledge graph concepts 

About Liberis

Liberis was founded and is backed by Blenheim Chalcot.

Liberis is on a mission to supercharge the power of small businesses around the world by delivering the financial products they need to grow, through our global network of partners. Before all else, Liberis is a technology company, connecting finance with small businesses. We use data to help partners understand their customers’ real-time needs and build technology that enables partners to offer tailored funding and financial products. To date, we’ve funded almost 50,000 small businesses with over $2bn - but we believe this is just the beginning. 

The Team

We are the Decision Analytics team sit with a goal to drive intelligent decision-making by applying advanced statistical analytics to a wealth of data. At the heart of the Risk function, our focus is to deliver high-quality instant decisions for our customers around the world.

Risk team is a globally team with offices in London, Nottingham and Atlanta US, covers Decision Analytics, Portfolio Management, Underwriting and Collections. We're on a mission to grow Liberis into the world's leading embedded business finance provider, and we're looking for a Decision Analytics Manager to help us make that happen!

The Role

Are you passionate about tackling complex challenges? Do you crave autonomy and the chance to innovate? If you're eager to make a real impact in finance that supports small businesses rather than just chasing profit, this is the perfect role for you.

You will own and evolve the automated credit decision policy across partners and products. You will be responsible for driving high auto-decision rates while maintaining competitive approval rates and robust risk performance. The role combines hands-on analytics with strategic ownership of acquisition decision strategies, monitoring frameworks, and model governance. This position is primarily a hands-on analytical role (70% individual contributor) while also mentoring and supporting junior team members (30% management). 

If you’ve got experience in an analytical role, using statistical tools to shape strategy, and the ability to turn data into clear, actionable insights, we want to hear from you.

What you’ll be doing

• Lead the development and optimisation of global decisioning strategies
• Own the automated decision policy framework and continuously enhance strategies to improve auto-decision rates and maintain competitive offerings.
• Work closely with the AI-ML team, playing a governance role in new model development, model approval and ongoing model monitoring
• Contribute to the development and enhancement of credit risk models
• Develop, own and enhance acquisition monitoring and performance reporting to track decision quality and risk performance
• Explore new and current data sources to optimise decisioning policy
• Mentor and support junior members within the team
• Collaborate with key risk stakeholders to maintain an acceptable risk level in a fast-evolving environment
• Represent Risk to the wider business, collaborating with Product and Commercial teams to unlock business value

What we think you’ll need

• 5+ years of experience in a relevant analytical, credit risk or decision science role
• 2+ years of experience working as a Decision Scientist or Data Scientist.
• A strong analytical mindset with a passion for turning complex data into insights
• The ability to communicate your findings clearly and effectively

Liberis is an equal opportunities employer. We welcome applications from all candidates, including individuals with disabilities and provide reasonable adjustments as required.

G-P helps organizations build global teams in minutes, not months. As part of this mission, we’ve created an indispensable AI agent for HR leaders, G-P Gia™ .

Gia is our AI-powered global HR agent that provides HR compliance guidance instantly. Built on over a decade of global employment and legal expertise and 100,000+ vetted articles, Gia analyzes and generates compliant documents and delivers the answers that HR leaders trust — reducing reliance on outside legal counsel and cutting compliance costs by up to 95%.

About The Position:

We’re building GIA — AI for General Counsel, in-house legal teams, and HR teams. GIA is a startup that demands extreme ownership, relentless execution, and zero tolerance for waiting on someone else to make the call. This role sits at the intersection of data science, data engineering, and product analytics. You build the pipelines, run the analysis, train the models, and — most importantly — tell us what the data means for the product. Not dashboards for the sake of dashboards. Insights that change what we build next.

What You Will Do:

• Build and own data infrastructure — pipelines, warehousing, ETL/ELT, data quality; make sure the foundation is solid
• Analyze product usage and user behavior — identify patterns, segment users, surface what matters from the noise; think like a product person, not just a data person
• Build models that ship — LLM-based systems, traditional ML (classification, clustering, NLP), evaluation frameworks; whatever the problem needs
• Define and track the metrics that matter — activation, retention, engagement, PQLs; connect data to product and GTM decisions
• Run experiments and measure impact — A/B tests, causal analysis, cohort studies; rigorous but fast
• Turn data into product conviction — you don’t just hand off charts, you tell the team what to do and why

What We Are Looking For:  

Minimum Requirements: 

• 5+ years across data science, data engineering, and analytics — you do all three, not just one
• Strong SQL and Python — complex queries, data modeling, scripting, analysis; this is your daily toolkit
• Databricks or equivalent modern data platform experience (Snowflake, BigQuery)
• LLM experience — fine-tuning, prompt engineering, embeddings, RAG, evaluation; not just API calls
• Traditional ML depth — classification, regression, clustering, NLP, feature engineering; you pick the right tool for the problem
• Product mindset — you filter signal from noise, understand user behavior, and connect analysis to product decisions
• Pipeline engineering — you build reliable, scalable data pipelines, not notebooks that break in production
• Clear communicator — you present findings to non-technical stakeholders with clarity and conviction

Preferred Qualifications: 

• Experience at an early-stage startup or as a founding data hire
• Built product analytics from scratch — instrumentation, event taxonomy, dashboards, self-serve reporting
• Legal or HR domain experience
• Experience with LLM evaluation and observability (tracing, scoring, drift detection)
• Familiar with dbt, Airflow/Dagster, Spark, or similar orchestration and transformation tools

How we evaluate

• Give you a real dataset and ask what you’d do with it — we want product thinking, not just technical chops
• Walk us through a time your analysis changed a product decision
• Design a data pipeline or model architecture on the whiteboard
• Show us how you’d instrument and measure a new feature from scratch

Interested? Reach out with an example of an insight you uncovered that changed what a team built.

Simtra BioPharma Solutions (Simtra) is a world-class Contract Development Manufacturing Organization, partnering with pharmaceutical and biotech companies to bring their sterile injectable products to market. With facilities in Bloomington, Indiana, US and Halle/Westfalen, Germany, we offer a wide range of delivery systems including pre-filled syringes, liquid/lyophilized vials, diluents for reconstitution, powder-filled vials and sterile crystallization.  

Our product types include biologics and small molecules, cytotoxics, highly potent compounds, diluents for reconstitution and vaccines – which are all directly injected into patients worldwide.  As such, there is a strong emphasis on quality and continuous improvement at Simtra.  We hold ourselves to the highest quality and regulatory standards.

While our primary focus is cGMP manufacturing, we offer many support services including formulation and development, lyophilization optimization, global regulatory support and secondary packaging.  Our teams are driven to help clients scale, innovate and bring life-changing medicines to patients worldwide.

Why join Team Simtra? Because we:

Make it HAPPEN – We bring a growth mindset to every opportunity, developing new skillsets and exceeding our expectations and those of our customers.

Make it TOGETHER – We work as one, respecting each voice and tapping into our unique strengths across teams—so we can solve problems in new ways.

Make it RIGHT – We hold ourselves to a high standard of excellence, fulfilling our commitments to the customer, their patients, and our team members.

Make it COUNT – We take pride in our day-to-day work, knowing the impact we make – taking on challenges big and small to improve patient health.

The role:

The Development Scientist role is responsible for independently managing development projects and investigating improvements of technology that advance formulation development, process development, and manufacturing at Simtra. This role is also responsible for training scientists in formulation and process development for injectable products. The scientist reports directly to the Global Senior Scientist.

The responsibilities:

• Independently design and manage research studies that demonstrate the scientific capabilities at Simtra, solve challenging process development problems for potential clients, and that can be published in peer-reviewed journals and presented at scientific meetings.
• Collaborate with scientists in Bloomington and Halle to introduce potential new clients to Simtra, learn about their molecule / project, and propose possible directions for developing the product.
• Collaborate with the development scientists at both sites to overcome possible challenges in the development of a product.
• Investigate possible solutions to challenges that may be encountered during product development.
• Develop and utilize a digital twin during conjugation and purification of antibody drug conjugates and possibly other areas of development and manufacturing.
• Develop, implement, and optimize techniques and procedures in the field of formulation and lyophilization development or analytical development and validation. Develop a deeply differentiated technical skill set to contribute to department capabilities for product development.
• Sought out by other teams and individuals to offer technical advice; may act as coach, mentor, supervisor, and technical advisor to junior members within the discipline.
• Implement new or improved techniques and procedures around specific tasks. Apply state-of-the-art techniques in the area of expertise to develop new or improved products.
• Apply specialized technical and theoretical knowledge in creative ways to a broad range of difficult problems. Contribute to technical feasibility analysis, which incorporates multiple disciplines where new and unproven methods and technologies are required. Generate innovative solutions to highly complex problems where little clear precedence exists. Incorporate advanced theories, methods and technologies from around the world to develop new innovative products/processes.
• Examine the use of predictive modeling and data analysis for formulation and process development to improve platforms for client projects.
• Utilize operational excellence and statistical tools to improve experimental design, process efficiency, or quality/compliance.
• In addition to having an in-depth knowledge and understanding of GxP and related regulations and guidance, is able to provide expert insights into such regulations so as to facilitate efficient product registration and/or is an active participant in the generation, review, adoption and interpretation of such regulations.
• Maintain current knowledge of relevant quality and other regulatory requirements related to research and development (product development, design and safety) to ensure compliance in all research, data collection and reporting activities.
• Investigate routes of collaborating with start-ups or other companies to obtain funding for research and development initiatives.
• Interact and collaborate with Sales, Marketing, and Program Management groups to professionally introduce potential new clients to Simtra Development and Pre-Commercial Services as well as other teams and capabilities.
• Develop and conduct scientific training programs in formulation and process development for BDEs, PM, and clients in collaboration with business development.

Required Qualifications:

• Bachelor's degree in Chemistry, Biochemistry, Pharmaceutical Science or a scientific discipline with at least 15 years of relevant experience, or MS with at least 10 years, or a scientist with a PhD in Pharmaceutical science, Chemical Engineering, or a scientific discipline.
• Lab experience includes research in GMP environment, leadership of technical teams, and project management experience is desirable.
• Computer proficiency in Microsoft Word, Excel, and Outlook and the ability to use enterprise software (examples include: TCU, Trackwise, etc.)
• Strong statistical skills and ability to use standard statistical software (examples include MiniTab, JMP) preferred.

Physical / Safety Requirements:

• Wear all PPE required by EHS (typically safety glasses, lab coat, gloves but may include a respirator).
• Duties may require overtime work, including nights and weekends
• Use of hands and fingers to manipulate office equipment is required
• Position requires sitting for long hours, but may involve walking or standing for periods of time.
• This position requires handling of laboratory chemicals
• Must be able to qualify for 20/25 corrected vision.

In return, you’ll be eligible for[1]:

• Day One Benefits
  • Medical & Dental Coverage
  • Flexible Spending Accounts
  • Life and AD&D Insurance
  • Supplemental Life Insurance
    • Spouse Life Insurance
    • Child Life Insurance
  • 401(k) Retirement Savings Plan with Company Match
  • Time Off Program
    • Paid Holidays
    • Paid Time Off
    • Paid Parental Leave and more
  • Adoption Reimbursement Program
  • Education Assistance Program
  • Employee Assistance Program
  • Community and Volunteer Service Program
  • Employee Ownership Plan
• Additional Benefits
  • Short and Long-Term Disability Insurance
  • Voluntary Insurance Benefits
    • Vision Coverage
    • Accident
    • Critical Illness
    • Hospital Indemnity Insurance
    • Identity Theft Protection
    • Legal and more
  • Onsite Campus Amenities
    • Workout Facility
    • Cafeteria
    • Credit Union

[1] Current benefit offerings are in effect through 12/31/26

Disclaimer

This job description is intended to provide the minimum knowledge, skills and abilities necessary to perform the job.  It may not be inclusive of all the duties and responsibilities of the job.  Simtra reserves the right to make modifications based on business requirements.

Equal Employment Opportunity

Simtra is proud to be an equal opportunity employer. Simtra evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.

Data Privacy

To learn more about Simtra's approach to data privacy, please review the Simtra Recruitment Platform Global Privacy Policy:  https://simtra.com/privacy-policy/

So, what’s the role all about?

At Actimize, we stop bad people from doing bad things. As part of our mission to enhance financial crime detection and prevention, we are building a next-generation Fin-Crime Investigation & Detection system powered by external data integrations and holistic insights. We are seeking a dynamic individual with high energy and drive to join our dynamic and growing X-Sight Monitor DS and AI team as a Specialist Data Analyst (AML).

 How will you make an impact?

NiCE Actimize is the largest and broadest provider of financial crime, risk and compliance solutions for regional and global financial institutions & has been consistently ranked as number one in the space

At NiCE Actimize, we recognize that all employee’s contributions are integral to our company’s growth and success. To find and acquire the best and brightest talent around the globe, we offer a challenging work environment, competitive compensation, and benefits, and rewarding career opportunities. Come share, grow and learn with us – you’ll be challenged, you’ll have fun and you’ll be part of a fast growing, highly respected organization.

This new SaaS platform will enable our customers (some of the biggest financial institutes around the world) to create solutions on the platform to fight financial crime.

Have you got what it takes?

• Overall, 8–12 years relevant three years of strong domain experience in Anti-Money Laundering
• Strong understanding of financial crime regulations, compliance, and risk management with a focus on AML Detection.
• Experience with SQL (Python – advantage).
• Experience in Product Development or Product Management advantage.
• Knowledge or familiarity with Cloud technologies advantage.
• Serve as an SME to support product requirements and domain knowledge. Analyse data and available information to deliver analytical features and logic for AML
• Strong problem-solving and analytical capabilities.
• Excellent verbal and written communication skills
• Ability to engage both technical and non-technical stakeholders effectively.

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10241
Reporting into: Group Manager
Role Type: Individual Contributor

The Role: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models.

WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Researcher. The person must have a strong understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. Candidates will have a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges.

WHAT YOU’LL BRING:

• Bachelor's (Hons), Master's or PhD degree in in a highly quantitative or highly analytical field e.g. Math, Physics, Computer Science or Financial Engineering from a leading university with excellent academic records are strongly preferred
• Have a research scientist mindset, i.e., be a deep thinker, creative, persevering, smart, a self-starter, etc.
• Knowledge of Linear Algebra, Statistics, Machine Learning
• Prior experience in Finance/Trading is a plus.
• Be competent in a programming language (Python, Unix)
• Possess good English language skills
• Have a strong interest in learning about worldwide financial markets
• Possess a relentless drive to succeed, supplemented by a strong work ethic

Staff Data Scientist – Supply Chain AI (Small Language Models)  

At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems. 

We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting. 

What Makes This Role Unique 

This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes. 

What You’ll Do 

• Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques 

• Embed supply chain knowledge into models by working closely with domain experts and product teams 

• Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks 

• Integrate models into products using custom Lambdas, and a Graph-based microservices architecture  

• Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships 

• Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets 

• Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE 

• Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation 
• Partner with engineering, product, and operations teams to ship impactful AI features end-to-end 

What We’re Looking For 

• Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations. 

• Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems) 

• Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights. 

• Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases 

• 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products 

• Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search. 

• Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment 

• Experience taking models from prototype to production 

• Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling 

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub. 

If you enjoy shipping AI that delivers measurable business value, this role is for you. 

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Position Summary 

As an Inizio Ignite Senior Analyst you will be a core member of client engagement teams, leading sophisticated analytics workstreams and owning the development of high-impact analytical deliverables. You will apply advanced analytical, coding, and modelling skills to solve complex business problems for life sciences clients, while contributing to methodological best practices across the data analytics team. 

A significant portion of this role will focus on commercial analytics and business intelligence, including marketing and sales analytics, real-world data analysis (e.g., claims and EHR), and the design and delivery of dashboards and data visualizations that support strategic and operational decision-making. 

In this role, you will work closely with case team leadership to design and execute analytics approaches, translate ambiguous business questions into structured analytical plans, and communicate insights clearly to both internal stakeholders and clients. 

Desired Skills and Experience 

The ideal candidate for the Senior Analyst position is a highly motivated, analytically rigorous individual with strong ownership mentality, excellent communication skills, and the ability to operate independently in a fast-paced consulting environment. 

• Proven analytic experiences and problem-solving skills (Master’s degree with a major in a related field of quantitative science e.g., engineering, computer/data science, statistics, mathematics, etc.)  

• Senior Analyst: Master’s degree plus 1-2 years of relevant work experience or PhD’s degree  

• Demonstrated expertise in processing and analyzing large datasets using SQL and Python/R/SAS; strong Excel skills (e.g., Power Query, VBA) a plus, with experience applying these skills to commercial analytics use cases such as marketing performance, sales effectiveness, patient journeys, and market dynamics 

• Strong foundation in statistical analysis and machine learning, including hypothesis testing, supervised and unsupervised learning, and model evaluation 

• Experience working with cloud-based data and analytics environments (e.g., AWS, Azure, Snowflake) 

• Proficiency in business intelligence, dashboarding, and data visualization using tools such as Tableau, Power BI, or Qlik Sense, with the ability to translate analytical results into clear, decision-ready insights 

• Experience working with real-world healthcare and life sciences datasets (e.g., claims, EHR, lab, provider, Rx, and payer data; sources such as Komodo, IQVIA, Symphony, Truven, Optum, Flatiron), particularly in commercial and market-facing analytics contexts; familiarity with omnichannel commercial analytics (e.g., HCP engagement, marketing mix, channel performance) is a plus 

• Ability to independently structure analyses, manage multiple priorities, and deliver high-quality work under tight timelines 

• Strong written and verbal communication skills, with the ability to explain complex analytical concepts to non-technical audiences 

• Experience working effectively as part of hybrid teams across multiple geographies, demonstrating strong collaboration, adaptability, and comfort operating in a global consulting environment  

Summary:
Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities:

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 10+ years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Address:

Bangalore Office  

Tekion India Private Limited 

6th, 7th & 8th Floor, Helium, Bagmane Solarium City, Doddanekkundi Village, KR Puram Hobli, East Taluk, Bangalore - 560037 

Chennai Office

Embassy Splendid Zone, Block 2, 9th floor, Velan Nagar, Arulmurugan Nagar, Old Pallavaram, Chennai, Tamil Nadu 600043

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

About the role:

We are hiring a Sr. Lifecycle Growth Manager to own activation end-to-end — the single highest-leverage stretch of our funnel. This is the work of recovering applicants who stall mid-application and converting approved customers who have not yet activated into paying policyholders. It is where intent either converts into revenue or leaks out, and it is the workstream with the most room to move the business in the next four quarters.

You will own the lifecycle strategy across two connected phases. In pre-approval, you will own the recovery layer for application drop-off — the sequences, nudges, and in-product interventions that bring stalled applicants back into the flow and through to approval. In ANA, you will own a fully personalized program segmented by where the approved customer dropped off and what the behavioral signals tell us about why.

This is a high-leverage IC role for someone who operates like a PM, thinks like a data scientist, and ships like an operator. You will run a high-velocity experimentation program, design product-led growth loops that go beyond email, and be the operational spine that turns activation OKRs into shipped work.

This is not a campaign-manager role. It is a role for someone who wants a seat at the strategy table, who can debate tradeoffs with a Director, and who is as comfortable writing SQL as writing a test plan.

What You'll Own:

Application Drop-Off Recovery

Own the lifecycle layer that recovers applicants who stall mid-application. You will map where drop-off concentrates across the application flow — saved-progress abandonment, step-level friction, medical exam scheduling hesitation, underwriting-window stalls — and build targeted recovery interventions for each leak point. You will work step-by-step, not in generic sequences: a customer who drops off at health disclosure gets a different treatment than one who drops off at payment details.

You will partner with Product and Engineering on in-product recovery surfaces (saved-progress resumption, step-specific support prompts) and own the outbound recovery motion across email, SMS, push, and Regal. Success is measured in step-to-step conversion lift and applicant-to-approved rate.

ANA Personalization

Own the ANA program with personalization as the core design principle, not a phase-two enhancement. The primary segmentation axis is drop-off point — a customer who was approved but never returned to view their quote needs a fundamentally different treatment than one who viewed a quote, selected a term, and abandoned at checkout. You will build distinct journeys for each drop-off cohort and layer secondary personalization on top: persona signals (price-sensitive, health-uncertain, comparison shopper, distracted/busy), term-length selected, quoted price band, and engagement recency.

You will own the evergreen ANA flow, term-length education moments, pricing transparency touchpoints, and social proof frameworks — all tuned to the specific drop-off point they are recovering. Success is measured in activation rate lift by cohort, not in email opens or aggregate sends.

Experimentation Engine

Own the end-to-end testing roadmap for activation. Move us from sporadic tests to a high-velocity program — 10+ well-designed experiments per quarter with clean hypotheses, appropriate power, and ruthless post-mortems. You decide what gets tested, you enforce statistical integrity, and you translate winners into roadmap changes. Incrementality tests, holdouts, frequency-cap experiments, and multivariate designs are in your default toolkit.

Product-Led Activation Growth

Activation is not an email problem. You will partner with Product and Engineering to design in-product interventions — application-step nudges, saved-progress recovery surfaces, pricing-transparency moments, term-length education, and post-approval decision support — that compound with our outbound channels. You will write PRDs, scope experiments with engineers, and measure feature adoption alongside channel metrics. You treat the product and the CRM as a single activation funnel.

Lifecycle Operations & Velocity

Turn strategy into shipped work. You will translate quarterly OKRs into concrete execution plans, architect the workflows that let the lifecycle operations execution team move fast with low error rates, and serve as the escalation point when ambiguous requirements or data issues block the team. You will co-own the planning table with US leadership during quarterly cycles and push back — with evidence — when a strategy is flawed or slower than it needs to be.

AI-Native Workflow Design

We are building an AI-native lifecycle function. You will use LLM-powered workflows to compress the time from hypothesis to shipped test — generating copy variants, QA'ing journeys, segmenting cohorts, and drafting briefs. This is not about using ChatGPT/ Claude occasionally; it is about designing systems where AI agents handle the execution layer so human time goes to strategy, analysis, and judgment calls.

Platform & Data

Act as the super-admin for our CRM stack (Iterable, Regal, and adjacent tooling). Partner with Engineering and Analytics to keep data pipelines clean, event schemas scalable, and deliverability pristine. You do not need to be the deepest technical expert on every platform, but you need to know enough to earn the team's respect and make the right architectural calls.

Duties and Responsibilities:

• You have 7-10+ years in lifecycle marketing, growth product management/ product-led-growth, or CRM at a B2C tech, fintech, SaaS, or marketplace company — with demonstrated impact on LTV, retention, or activation metrics that mattered to the business.
• You are fluent in SQL and understand the data in and out. You do not wait for an analyst to tell you whether a campaign worked — you pull the data yourself, segment the cohort, and come back with the answer. You understand statistical significance, power analysis, cohort retention curves, and the difference between a lift that is real and a lift that is noise.
• You have shipped PLG experiments, not just email campaigns. You have written a PRD, worked through a trade-off with an engineer, and measured in-product feature adoption. You understand that the highest-leverage lifecycle work often lives inside the product.
• You are hands-on with enterprise CRM platforms — Iterable, Braze, Customer.io, or similar. You can build a complex multi-branch journey without hand-holding, and you can debug why a campaign is not firing without escalating to a vendor rep.
• You communicate like a senior operator. You can debate strategy with a Director, write a decision memo, and hold your ground when you disagree — while staying open when the counterpoint is stronger. You default to direct, concise, written communication and flag ambiguous items explicitly rather than resolving them with unspoken assumptions.
• You have worked across time zones with a US-based manager and know how to make asynchronous collaboration work — owning hand-offs, writing clear updates, and protecting the golden-hour overlap for high-bandwidth decisions.

Nice to Have

• Experience at a fintech, insurtech, or regulated-vertical company where compliance shapes the lifecycle program
• Hands-on background leading an ESP or CDP migration (Iterable, Braze, Responsys, Salesforce Marketing Cloud)
• Experience in a two-sided marketplace or high-volume B2C environment
• Prior PM or PM-adjacent role — you have owned a roadmap, not just a campaign calendar
• Working familiarity with experimentation platforms (Optimizely, Statsig, LaunchDarkly, or in-house feature flagging)
• Basic HTML/CSS fluency — enough to debug a rendering issue without waiting on a developer

How We Work

We move fast, ship small, and measure everything. We prefer shipping an imperfect test this week over a perfect one next quarter. We over-communicate in writing, treat post-mortems as sacred, and are genuinely allergic to work that does not connect back to a revenue or retention number. We believe the best lifecycle teams in the world will be AI-native by default within the next two years, and we are building accordingly.

If you want to run a campaign calendar, this is the wrong role. If you want to architect a growth engine, let's talk.

#LI-Hybrid

#LI-NG1

Role Overview

We are seeking a Principal Applied Scientist to be the highest-level AI technical authority on the team. This role is above the Applied Scientist level — you set the AI research and engineering direction, own the agentic system architecture, define the eval framework standards, and operate as the primary interface to the external AI research community and internal platform AI leadership. You will combine deep research rigor with relentless production focus: every AI capability you design ships, gets measured, and improves based on evidence.

You are the person who answers: "Is this AI approach the right one, and how do we know when it's working"

Key Responsibilities

• Own the agentic system architecture: define the multi-agent coordination patterns, MCP tool taxonomy, intent-to-skill routing logic, policy enforcement design, and memory management strategy across all AI workflows on the platform.
• Lead the AI evaluation framework: design the golden dataset structure, define eval metrics (RAG retrieval quality, scoring accuracy, LLM response correctness, agentic workflow success rate), and own the CI/CD AI eval pipeline that gates every AI capability release.
• Drive the RAG architecture strategy: chunking strategies for MongoDB and Elasticsearch-indexed documents, embedding model selection and fine-tuning, retrieval reranking design, and hallucination mitigation patterns.
• Own the LLM integration architecture: prompt engineering standards, LLM gateway usage policies, context window management, streaming response patterns, and model version governance.
• Lead applied research initiatives: identify novel techniques (RLHF, Constitutional AI, multi-modal, sparse retrieval) that are practically applicable to automotive retail intelligence use cases and prototype them rigorously in Python.
• Define the hexagonal AI adapter contract standard: the formal interface specification between Python AI services and Java domain cores — ensuring AI infrastructure remains swappable without domain logic changes.
• Act as primary technical interface to platform AI leadership (LLM Gateway, ML Platform, Agentic Engine) — influencing platform roadmap based on teams practical requirements.
• Mentor the Applied Scientist and ML Architect; conduct technical reviews of AI system designs, eval frameworks, and research approaches.
• Publish, present, or contribute to open-source where appropriate — representing Tekion's AI engineering excellence externally.

Skills & Qualifications

• 10+ years of applied AI/ML experience with at least 3 years at Staff or Principal level — a track record of shipping AI systems that measurably changed business outcomes.
• Deep expertise across: LLM fine-tuning and alignment, RAG system design (chunking, embedding, retrieval, reranking), agentic frameworks (LangGraph, CrewAI, AutoGen), and MCP tool design.
• Python mastery: PyTorch, Hugging Face Transformers, LangChain/LangGraph, scikit-learn, and production ML serving tooling.
• Strong understanding of distributed AI systems: Elasticsearch-backed vector search, Redis/Aerospike serving, Cosmos DB for AI event logging, and Kafka-based feature pipelines.
• Proven ability to design formal eval frameworks for AI systems — not just accuracy metrics but business aligned quality gates.
• Experience defining and enforcing hexagonal adapter contracts between AI services and domain service layers in production systems.
• Track record of communicating complex AI system design to non-technical stakeholders, influencing product roadmaps, and driving cross-team alignment. 

Good to Have

• Publications or significant open-source contributions in NLP, information retrieval, or agentic systems.
• Experience with Constitutional AI, RLAIF, or preference optimization techniques (DPO, PPO).
• Familiarity with multi-modal AI and its application to automotive retail data (images, documents, tabular data fusion).
• Prior experience in a product-focused AI role at a SaaS or platform company — not purely research. 

Perks & Benefits

• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

Turn Your Expertise Into Impact at Scale

At Interview Kickstart, we don’t just teach—we transform careers. For our lead instructor role, we’re looking for engineers who want to go beyond building systems—to shape the people who build them.

Our practitioner-led approach means every class is taught by experts who’ve built at scale and cleared top hiring bars at FAANG+ companies. With a global learner base, expanding enterprise partnerships, and a fast-growing Agentic AI curriculum, this is a unique opportunity to collaborate with top talent, influence cutting-edge learning, and help define the gold standard for AI education.

Who You Will Be Teaching

Our learners are experienced professionals (5+ years) from software engineering, data science, and related fields, aiming to transition into ML Engineering, Applied Scientist, and AI roles at top-tier companies. They’re highly motivated and technically strong, seeking deep, practical learning—not basics. They value instructors who can connect theory to real-world systems, share insider hiring insights, and provide mentorship rooted in hands-on industry experience.

Key Responsibilities

A. Teaching & Learner Engagement

• Deliver high-impact live sessions on Agentic AI & Machine Learning
• Lead small-group coaching sessions for hands-on problem-solving and doubt resolution
• Run assignment reviews to reinforce concepts and deepen understanding
• Conduct mock interviews (ML System Design, Coding) with actionable feedback
• Provide 1:1 mentorship on career transitions and interview prep
• Host cohort orientations to drive engagement and set expectations

B. Curriculum Development & Review

• Own end-to-end curriculum for Agentic AI/ML (content, assignments, projects)
• Continuously update material with latest tools, trends, and industry practices
• Design evaluation frameworks, rubrics, and assessments
• Collaborate cross-functionally to ensure quality and learner outcomes

C. Marketing & Thought Leadership

• Create masterclasses, webinars, and video content to drive learner growth
• Publish and review technical content (blogs, social, insights)
• Represent IK at events, meetups, and conferences

D. Team Development & Quality

• Mentor and onboard instructors and TAs; set quality benchmarks
• Collaborate to continuously raise teaching standards across the platform
• Leverage learner feedback, ratings, and data to improve delivery quality

What We’re looking for

• 5+ years in Software/ML Engineering (Tier-1 / FAANG+ preferred)
• Strong in DSA, System Design, and ML Systems
• Hands-on experience in Agentic AI / ML (production-level)
• Passion for teaching, mentoring, and driving learner success
• Ability to simplify complex concepts clearly and engagingly
• Strong communication skills and learner empathy

You’d stand out if you have:

• Prior Teaching, mentoring, or content creation experience
• Hiring/interviewing experience at top tech companies
• Research, open-source, or advanced degree in a relevant field
• At the core: a desire to create real impact by shaping careers at scale.

Most Importantly - What’s in it for you?

• Real Impact – Help professionals land top roles and see your impact firsthand
• Shape AI Education – Build and evolve a cutting-edge Agentic AI/ML curriculum
• Remote & Global – Work from anywhere, teach learners worldwide
• Learn From the Best – Collaborate with 700+ instructors from top tech companies
• Top-Tier Pay – Industry-leading compensation with strong growth
• Build Your Brand – Teach, write, and speak on a global stage
• Unlimited Growth – Evolve into leadership and high-impact roles

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.

The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…

What you will be doing?

As a Data Scientist, your primary role revolves around leveraging Python and SQL to conduct data science modelling, employing statistical and machine learning algorithms to derive actionable insights. Your responsibilities will encompass:

• Data Modeling: Developing and implementing sophisticated data science models to extract valuable insights from complex datasets.
• Algorithm Implementation: Applying statistical and machine learning algorithms to solve business problems and enhance decision-making processes.
• Visualization: Utilizing visualization tools like Tableau and PowerBI to present findings in a compelling and understandable manner.
• Cloud-Based Deployment: Deploying models on cloud platforms such as MS Azure, GCP, and AWS, optimizing their functionality and scalability.

What we are looking for?

• Proficiency in Python, SQL, data science modeling, and statistical analysis.
• Strong grasp of ML algorithms and their implementation in real-world scenarios.
• Experience in visualization tools like Tableau and PowerBI, along with knowledge of deploying models on cloud platforms (MS Azure, GCP, AWS).
• Proven problem-solving skills and a solution-oriented mindset.
• Excellent communication skills to collaborate effectively within teams and with stakeholders.
• Strong business acumen with an interest in business-facing roles.
• Adaptability and a start-up mentality to thrive in a dynamic environment.
• Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms.
• Successful candidates often possess Computer Science, Electronics and Communication Engineering degrees.

MariaDB is making a big impact on the world. Whether you’re checking your bank account, buying a coffee, shopping online, making a phone call, listening to music, taking out a loan or ordering takeout – MariaDB is the backbone of applications used everyday. Companies small and large, including 75% of the Fortune 500, run MariaDB, touching the lives of billions of people. With massive reach through Linux distributions, enterprise deployments and public clouds, MariaDB is uniquely positioned as the leading database for modern application development.

About the Role

We're hiring a Senior Data Scientist with strong programming skills, a deep command of analytical methods, and the ability to turn complex data into clear business insights. You'll join a small, highly skilled team where your work has a direct impact on how the business operates and makes decisions.

This is a hands-on, high-autonomy role. You'll work across the full data stack-writing sophisticated SQL in BigQuery and MariaDB, building automation and tooling in Python, and leveraging AI-powered tools like Windsurf, Gemini, and Claude to work faster and smarter. You'll be expected to understand how data is structured end-to-end, from source systems through to the warehouse, and to know which analytical approach fits which business question.

You'll also be a key communicator-translating complex data into clear narratives for stakeholders across the organization. We need someone who can operate independently, manage their own priorities, and continuously raise the bar on what's possible with our data. If you have a genuine passion for analytics, a GitHub full of projects, and you're the kind of person who's always learning the next thing-we'd love to hear from you.

Key Responsibilities

• Apply the right analytical methods-statistical analysis, regression, clustering, forecasting, classification-to solve real business problems at scale
• Design and build end-to-end analytical solutions-from data extraction in BigQuery and MariaDB to actionable insights and automated reporting
• Develop and maintain data pipelines, analytical frameworks, and tooling using Python and SQL
• Use AI-powered development tools (Windsurf, Gemini, Claude, Cursor) to accelerate experimentation, code generation, and analysis
• Leverage the latest AI features and tools (LLMs, embeddings, generative AI) to augment and automate analytical workflows
• Build lightweight applications and APIs (FastAPI) to put models and insights into the hands of stakeholders
• Own the data architecture decisions within your domain-schema design, data modeling, and pipeline reliability
• Communicate results, trade-offs, and recommendations clearly to both technical and business audiences
• Map and improve business processes through data-driven analysis and process design

Requirements & Qualifications

• 7+ years of professional experience in data science, advanced analytics, or a quantitative field
• Expert-level SQL - deep fluency in BigQuery and MariaDB or similar data platforms; you understand query optimization, partitioning, and data modeling
• Strong Python and/or JavaScript skills - production-quality code, not just notebooks; experience with modern data and ML libraries
• Deep understanding of analytical methods - regression, clustering, time series, A/B testing, classification; you know when to apply what and why
• Solid understanding of data architecture - how warehouses, lakes, and pipelines are designed; how to structure data for both analytical and ML workloads
• Proficiency with AI-powered development tools - Windsurf, Gemini, Claude, Cursor, or similar; you leverage AI assistants as a core part of your workflow
• Excellent communication skills - you present complex technical work in a way that drives decisions
• Self-managing and self-sufficient - you set your own priorities, unblock yourself, and deliver without hand-holding
• Relentlessly curious and ambitious - you're always learning, always building, always improving
• A public GitHub profile showcasing your projects, experiments, or contributions

Nice to Have

• Experience with Next.js or modern frontend frameworks for building data-facing applications
• FastAPI experience for serving models or internal tooling
• Background in business process analysis or operational process design
• Experience working across multiple business departments (Finance, Marketing, Sales, Operations, Engineering) - broad organizational exposure is a big plus
• Experience with JSON-based data formats, APIs, and integration patterns
• Understanding of Docker and Kubernetes - containerization and cluster orchestration experience is a big plus

Benefits & Culture

• Globally distributed team environment
• Remote or hybrid work options (location-dependent)
• Challenging projects with company-wide impact
• Competitive compensation, 25 days paid annual leave, plus holidays
• A culture that values curiosity, clean engineering, and people who genuinely love what they do

Location – India (remote)

Travel – Flexible for adhoc travel

What's in it for you?

Impact the world of technology by pushing the boundaries of technology and business models, working at MariaDB, plc. Be part of a game-changing organization that encourages outside-the-box thinking, values empowerment, and is truly shaping the future of the software industry. 

You’ll be collaborating with high-caliber colleagues around the world, offering unparalleled learning and growth opportunities. We provide a very competitive compensation package, 25 days paid annual leave (plus holidays) and a massive degree of flexibility and freedom, and more.

Salaries for candidates outside the U.S. will vary based on local compensation structures.

How to Apply

If you are interested in this position, please submit your application along with your CV/Resume through our ATS Greenhouse on our MariaDB Careers site.

• At MariaDB we celebrate the diverse experiences and perspectives of our employees because this drives innovation and success. MariaDB is an equal opportunity employer dedicated to creating a welcoming and inclusive workplace for everyone.
• MariaDB does not sponsor work visas or relocation.
• MariaDB is committed to providing accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.
• MariaDB will not accept agency resumes without a prior contractual agreement with HR. Please do not forward resumes to any recruiting alias or employee directly. MariaDB is not responsible for paying any fees associated with any unsolicited submitted CV/Resumes.

CSQ326R35

Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Minimum of 5+ years of relevant experience as a Data Scientist preferably working in a consulting role
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

We are seeking an experienced and highly skilled Senior Data Scientist to lead our efforts in optimizing ad display on native Android surfaces. In this role, you will design and implement data-driven strategies to maximize ad effectiveness, user engagement, and revenue. You will collaborate closely with product managers, engineers, and cross-functional teams to drive innovation, improve ad relevance, and ensure a seamless user experience.

As a Senior Data Scientist, you’ll get to:

• Develop and refine data-driven ad optimization strategies tailored to native Android environments, focusing on user engagement, personalization, and revenue uplift.
• Design, implement, and improve predictive models for ad targeting, recommendation, and bidding strategies using cutting-edge machine learning and statistical techniques.
• Lead the design and analysis of experiments to test ad placements, formats, and targeting methods. Use data from A/B tests and multivariate testing to validate hypotheses and inform decisions.
• Analyze user behavior patterns to understand engagement and dropout points, leveraging insights to optimize ad positioning, timing, and relevance.
• Partner with product managers, engineers, designers, and marketing teams to align ad strategies with business objectives and user experience goals. Communicate insights and recommendations effectively to both technical and non-technical stakeholders.
• Ensure the scalability of ad models across a wide range of Android devices and varying network conditions. Work closely with engineering teams to deploy and monitor models in a production environment.
• Provide mentorship and guidance to junior data scientists, fostering a collaborative and innovative team environment. Lead by example in developing high-quality, scalable solutions for complex ad optimization challenges.

You’ll be a good fit if you have:

• PhD (preferred) or Master's Degree (required) in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
• 6+ years of experience in data science or machine learning, with a strong focus on ad technology or user experience optimization.
• Demonstrable experience in working with ad serving, ad tech stacks, and optimization techniques, especially within Android or mobile ecosystems.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, or similar).
• Advanced proficiency in Python, or Kotlin.
• Experience with data processing and pipeline tools (e.g., Spark, Hadoop, Airflow).
• Deep understanding of A/B testing, causal inference, and other experimentation methods.
• Familiarity with ad tech, programmatic advertising, and user behavior metrics, particularly in the context of mobile and Android platforms.
• Excellent analytical, problem-solving, and communication skills. Proven ability to articulate complex data science concepts to stakeholders across different domains.

 Nice to have: 

• Previous experience optimizing ad displays on native mobile or Android surfaces.
• Familiarity with the Android SDK and understanding of native Android UI/UX design principles.
• Knowledge of reinforcement learning, multi-armed bandit models, and contextual targeting techniques.

This role is based at our Bengaluru, India office and follows a Hybrid schedule that will be aligned with our Return to Office guidelines.

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Staff Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Senior Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Senior Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 5+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.

Offices: New York | Dallas | San Francisco | Lima | Bengaluru

The below role is for our Bengaluru office.

About the Role:

You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you.

Function:  Data Science and Analysis → Data Science / Machine Learning

Desired Skills & Competencies:

• Strong learning acumen
• Team Management
• High sense of ownership
• Ability to work in a fast-paced and deadline-driven environment
• Loves technology
• Highly skilled at Data Interpretation
• Problem solver
• Good exposure to machine learning concepts and algorithms
• Must be fluent with any one of Python, R, Java
• Strong in statistical & machine learning concepts
• Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn
• Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS)

Responsibilities:

• Hypothesis testing, insights generation, root cause analysis, factor analysis
• Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms
• Test/train the model, Improve Model accuracy, Monitor model performance
• Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), performing EDA

Desired Experience & Education:

• 3 - 5 years of relevant Machine Learning experience.
• B. Tech from Tier-1 college / M.S or M. Tech is preferred in Computer Science, Information Technology, or similar degree.

Tekion seeks an exceptionally talented and seasoned Staff / Lead Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale.  
 
Key Responsibilities 

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges. 

• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions. 

• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives. 

• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services. 

• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation. 

• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth. 

• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership. 

• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI 

Core Competencies & Technical Expertise 

            The successful candidate will demonstrate mastery in the following areas: 

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI. 

• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data. 
   
   

Deep Learning: 

• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch. 

• Extensive experience implementing advanced neural network architectures. 

• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g.,spaCy) methodologies. 

• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications. 

Technical Proficiencies: 

• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous. 

• Proficiency with cloud computing platforms (GCP, Azure, AWS). 

• Expertise in experimental design (A/B testing, causal inference). 

• Proficient in version control systems (Git). 

Required Qualifications 

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field. 

• A minimum of 7 - 9 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value. 

• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach. 

• Proven experience in programming, data manipulation, and building models in a business context. 

• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences. 
   

Ideal Candidate Profile 
 

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving. 

• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable. 

• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred. 

• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences. 

• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams. 

• A commitment to continuous personal and team development within a collaborative, high-performance culture. 

Perks and Benefits

• Competitive compensation 

• Generous stock options 

• Medical Insurance coverage 

• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies 

Role Overview

We are hiring Microsoft Certified Trainers (MCTs) based in India to deliver official Microsoft courseware to enterprise learners as part of Interview Kickstart’s growing skilling ecosystem. As an MCT at IK, you will bring your deep Microsoft technology expertise to live, instructor-led training sessions for professionals across industries.

This is a part-time, remote engagement suited for experienced Microsoft practitioners and trainers looking to expand their impact.

Key Responsibilities

• Deliver official Microsoft courseware in live, instructor-led formats (virtual and in-person as needed)

Train enterprise professionals on Microsoft technologies including Azure, Microsoft 365, Power Platform, Dynamics 365, and AI/Copilot tools

• Design and adapt training content to match the learning needs and skill levels of diverse enterprise audiences
• Guide learners through hands-on labs, exercises, and real-world use case scenarios
• Assess learner progress and provide constructive feedback aligned with Microsoft certification pathways
• Stay current with the latest Microsoft product updates, courseware revisions, and certification changes
• Collaborate with IK’s curriculum and delivery teams to ensure quality and consistency of training outcomes

What You’ll Teach

Depending on your area of specialisation, training delivery may cover one or more of the following Microsoft domains:

Microsoft Azure & Cloud

• Azure fundamentals, administration, architecture, and security
• Azure AI services, Azure OpenAI, and intelligent cloud solutions
• DevOps, infrastructure, and cloud-native development on Azure

Microsoft 365 & Productivity

• Microsoft 365 administration, compliance, and endpoint management
• Microsoft Teams, SharePoint, and collaboration tools for enterprise
• Microsoft 365 Copilot and AI-assisted productivity workflows

Power Platform & Business Applications

• Power BI, Power Apps, Power Automate, and Power Virtual Agents
• Dynamics 365 for CRM, ERP, and business operations
• Low-code/no-code application development and automation

Security, Compliance & Identity

• Microsoft Security, Compliance, and Identity solutions
• Zero Trust architecture and enterprise security frameworks

Training will cover the following Azure AI/ML certification tracks (Phase 1):

Must-Have Qualifications

• Active Microsoft Certified Trainer (MCT) status in good standing
• Minimum 2 relevant Microsoft certifications in your area of expertise
• Should have experience working with Azure Labs
• 3+ years of hands-on experience with Microsoft technologies in enterprise environments
• Proven experience delivering instructor-led training (corporate, academic, or self-organised)
• Strong communication skills in English; ability to simplify complex technical concepts for mixed audiences
• Familiarity with virtual training delivery tools (Teams, Zoom, LMS platforms)

Good to Have

Profile Summary: An aspiring and skilled Data Scientist, eager to apply and grow expertise in algorithms and data analysis. Proficient in leveraging Python, Jupyter, and GCP services to analyse and extract insights from complex datasets. Will support key data science initiatives, collaborating with senior data scientists to develop and optimise solutions that drive business value. Focused on contributing to high-impact projects, while building institutional knowledge. 

Key Skills: (Sr Analyst) 

• Upto 3 yrs 

• Strong programming skills in Python and experience using Jupyter notebooks for data analysis and visualisation. 

• Familiarity with GCP services such as BigQuery, Google Cloud Functions and Vertex AI. 

• Solid understanding of machine learning techniques and their application in data activation solutions, including supervised and unsupervised learning, classification, and regression models. 

• Proficiency in data manipulation and cleaning using libraries like Pandas and NumPy, ensuring high-quality datasets for analysis and modelling. 

• Good communication skills, with the ability to articulate findings and support senior team members in presenting insights. 

Description: 

• Assist in the development and implementation of data science algorithms for various strategic initiatives  

• Collaborate with senior data scientists and cross-functional teams to design and execute A/B tests, analysing results to contribute actionable insights and recommendations. 

• Utilise Python and Jupyter notebooks to preprocess and analyse large datasets, identifying trends and patterns that inform strategic decision-making. 

• Contribute to the optimisation of marketing campaigns and other business processes through data-driven approaches. 

• Support the presentation of findings and insights to internal stakeholders, ensuring clarity and impact. 

• Engage in ongoing learning and development to enhance data science capabilities and contribute to team growth. 

Education: 

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline. 

Ideal Certifications: 

• Python for Data Science (Coursera) 

• Google Cloud Machine Learning Engineer (Associate) 

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

#LI-GOC

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

Profile Summary: An aspiring and skilled Data Scientist, eager to apply and grow expertise in algorithms and data analysis. Proficient in leveraging Python, Jupyter, and GCP services to analyse and extract insights from complex datasets. Will support key data science initiatives, collaborating with senior data scientists to develop and optimise solutions that drive business value. Focused on contributing to high-impact projects, while building institutional knowledge.

Key Skills: (Sr Analyst)

• Upto 3 yrs
• Strong programming skills in Python and experience using Jupyter notebooks for data analysis and visualisation.
• Familiarity with GCP services such as BigQuery, Google Cloud Functions and Vertex AI.
• Solid understanding of machine learning techniques and their application in data activation solutions, including supervised and unsupervised learning, classification, and regression models.
• Proficiency in data manipulation and cleaning using libraries like Pandas and NumPy, ensuring high-quality datasets for analysis and modelling.
• Good communication skills, with the ability to articulate findings and support senior team members in presenting insights.

Description:

• Assist in the development and implementation of data science algorithms for various strategic initiatives
• Collaborate with senior data scientists and cross-functional teams to design and execute A/B tests, analysing results to contribute actionable insights and recommendations.
• Utilise Python and Jupyter notebooks to preprocess and analyse large datasets, identifying trends and patterns that inform strategic decision-making.
• Contribute to the optimisation of marketing campaigns and other business processes through data-driven approaches.
• Support the presentation of findings and insights to internal stakeholders, ensuring clarity and impact.
• Engage in ongoing learning and development to enhance data science capabilities and contribute to team growth.

Education:

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.

Ideal Certifications:

• Python for Data Science (Coursera)
• Google Cloud Machine Learning Engineer (Associate)

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

#LI-GOC

Technical Expertise:

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.

Applied Problem-Solving:

• Mandatory skill - Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.
• Mandatory skill - Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration:

• (Preferred) Proven ability to lead and mentor a junior applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Education & Experience:

• 3+ years of hands-on experience in applied machine learning and data science with Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field or appropriate experience.
• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

•  Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 5+ years of hands-on experience in applied machine learning and data science.

Tekion is pioneering the digital transformation of the automotive industry, a sector that has remained largely undisrupted for over five decades. Our flagship platform, the Automotive Retail Cloud™, is the first and fastest cloud-native solution of its kind, fundamentally re-engineering the end-to-end automotive retail experience. By leveraging vast datasets, sophisticated machine learning, and advanced AI, we are creating a seamlessly integrated ecosystem connecting OEMs, retailers, and consumers. We are a globally distributed team of technologists and innovators dedicated to solving complex, high Impact challenges.

The Position

Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
• Extensive experience implementing advanced neural network architectures.
• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
• Proficiency with cloud computing platforms (GCP, Azure, AWS).
• Expertise in experimental design (A/B testing, causal inference).
• Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 11-14 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

Senior Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 8+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 8+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Pune / Hyderabad 

Lead Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 10+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 10+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.

• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Hyderabad 

Senior Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 8+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 8+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Pune / Hyderabad 

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The Opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The Role  

As a Senior Data Scientist, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 4+ years of experience, a growth mindset and a drive to make a lasting impact. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role & Responsibilities:

Generative AI Innovation & Strategy

• Lead GenAI Initiatives: Spearhead the identification of business scenarios where Generative AI (LLMs, GANs, Diffusion models) can be effectively applied to create tangible value.
• R&D & Prototyping: Research, design, and prototype cutting-edge approaches, exploring existing scientific research to inform solution development.
• Feasibility Analysis: Evaluate the technical and economic feasibility of Generative AI solutions for real-world client use cases.
• Vision Shaping: Collaborate with Product Managers and stakeholders to shape a clear, forward-looking vision of AI technology and its practical applications.

Technical Execution & Implementation

• End-to-End Development: Implement and validate AI solutions for diverse business challenges, writing production-ready code using best engineering practices.
• Optimization: Optimize deep learning models for production environments to ensure scalability and latency requirements are met.
• Cross-Functional Collaboration: Collaborate closely with the ML Engineering team throughout all stages of the lifecycle, from initial research to final implementation.
• Data Strategy: Oversee the data mining process, including data collection, cleansing, and exploratory analysis to support model training and fine-tuning.

Must Have

To be considered for this role, you must meet the following essential qualifications: 

• Total Experience: Minimum of 4+ years in Data Science and Analytics.
• Specialized Experience: Minimum 3+ years focused specifically on developing generative models (LLMs, GANs, VAEs, Diffusion models) and Deep Learning.
• Education: Bachelor’s or Master’s Degree in Computer Science, Mathematics, Applied Statistics, or a related field.

Technical Skills

• Core AI/ML: Expertise in Computer Vision and NLP, with specific experience handling multimodal data (images, text, audio).
• GenAI Stack: Familiarity with Gemini, OpenAI GPT-x, open-source LLMs (Llama, Mistral, etc.), and experience in fine-tuning models (PEFT, LoRA).
• Retrieval-Augmented Generation (RAG): Expertise in designing RAG architectures to ground LLM responses in proprietary data.
• Vector Databases: Proficiency with vector stores such as Pinecone, Milvus, Weaviate, or ChromaDB for efficient semantic search and retrieval.
• Prompt Engineering: Advanced skills in prompt optimization, chain-of-thought reasoning, and framework usage (e.g., LangChain, LlamaIndex).
• Programming: Strong programming skills in Python with proven ability to write clean, production-ready code.
• Frameworks: Proficiency with deep learning frameworks such as PyTorch or TensorFlow.
• Cloud: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).

Soft Skills

• Communication: Excellent fluency in English (B2+ or higher) with the ability to explain complex technical concepts to non-technical audiences.
• Problem Solving: A strategic thinker capable of devising holistic solutions for complex customer issues.

Nice to Have (Preferred Qualifications)

• Experience with MLOps tools (e.g., MLflow, Kubeflow) and practices for deploying and monitoring AI models.
• Responsible AI: Knowledge of AI ethics, bias detection, and safety guardrails (e.g., NeMo Guardrails) for deploying LLMs securely.
• API Development: Experience wrapping models in APIs using FastAPI or Flask for integration with frontend applications.
• Knowledge of Reinforcement Learning (RLHF) and self-supervised learning approaches.
• Experience with emerging Generative AI architectures.

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

 The Benefits  

This is a Full-Time position based in Bengaluru.

Beyond a competitive compensation package, we offer: 

• Flexibility, with hybrid work options (country-dependent) 
• Learning and development, with access to cutting-edge tools, training and industry experts.

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. 

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses ending in @valtech.com. 

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

We are growing our data science team and looking for a passionate individual who can bridge the gap between business problems and data solutions.

Key Responsibilities

• Own the end-to-end problem-solving lifecycle: business context → data → AI-driven insights → outcomes
• Work directly with customers and internal teams to understand business problems and define solutions
• Analyze large, complex datasets using SQL and Python
  
• Design and deliver AI-powered analytics solutions using Tellius
• Translate ambiguous business problems into structured analytics or AI workflows
  
• Build and demo insight-driven dashboards and narratives for business users
• Partner closely with Product, Engineering, and GTM teams
  
• Present insights and recommendations confidently to business and technical stakeholders
  

Must-Have Skills

• 3+ years of experience in data science, solutions engineering, or analytics consulting
• Strong hands-on skills in SQL and Python
  
• Experience with cloud data platforms (Snowflake, Databricks, Redshift)
• Hands-on experience with LLMs and AI agents, including prompt engineering, RAG pipelines, AI agent workflows, and deploying AI-driven solutions beyond basic ChatGPT usage.
• Understanding of agentic AI concepts: memory, tool usage, orchestration, multi-step reasoning
• Experience with analytics platforms such as Tableau, Power BI, and ThoughtSpot (you understand what Tellius replaces)
• Domain exposure in pharma commercial analytics, CPG/retail analytics, or FP&A (at least one)
• Strong storytelling, presentation, and stakeholder management skills
• Comfortable in customer-facing roles
  

Good to Have

• Prior experience in an analytics or AI SaaS product company
  
• Exposure to enterprise decision workflows
  
• Experience demoing or solutioning for clients

Who You Are

• Curious, analytical, and business-minded
• Comfortable working in ambiguity
• Excited about AI-native analytics and agentic systems
  
• Strong communicator who can turn insights into action

Why Join Tellius

• Build next-gen, AI-native analytics products
  
• Work on real customer problems with measurable impact
• Collaborate with top talent across AI, data, and product
• Fast growth, high ownership, and strong learning opportunities

Staff Data Scientist – Supply Chain AI (Small Language Models)  

At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems. 

We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting. 

What Makes This Role Unique 

This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes. 

What You’ll Do 

• Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques 

• Embed supply chain knowledge into models by working closely with domain experts and product teams 

• Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks 

• Integrate models into products using custom Lambdas, and a Graph-based microservices architecture  

• Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships 

• Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets 

• Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE 

• Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation 
• Partner with engineering, product, and operations teams to ship impactful AI features end-to-end 

What We’re Looking For 

• Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations. 

• Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems) 

• Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights. 

• Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases 

• 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products 

• Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search. 

• Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment 

• Experience taking models from prototype to production 

• Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling 

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub. 

If you enjoy shipping AI that delivers measurable business value, this role is for you. 

General Application - We want to hear from you!!

Not seeing a role that matches your exact experience? We still want to connect!

Whether you're a seasoned data scientist, an up-and-coming analyst, a tech-savvy project manager, or passionate about enabling people behind the scenes in HR, marketing, or operations—ProCogia is always looking for smart, driven, and collaborative individuals to join our growing team.

Who You Might Be

• A curious problem-solver who thrives in fast-paced, dynamic environments
• A team player who values diversity, equity, and inclusion
• Someone with a background in:
• Data Science, Engineering, or Analytics
• Project or Program Management
• Software Development
• Consulting or Client Success
• HR, Operations, or Marketing

If you're passionate about data, people, and innovation—we want to hear your story.

Please note: While you may not hear from us right away, we truly value every application. We’ll keep your information on file and reach out if and when there’s a role that matches your skills and experience. Thank you for considering a future with ProCogia!