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!

About the Opportunity

User Store is the foundational intelligence platform of InMobi Group. The Senior PM in this role will define its long-term strategy, shape how user signals are transformed into AI-ready intelligence, and directly influence how InMobi empowers its partners globally.

At its core, this role is about turning scale into intelligence. InMobi processes billions of real-time signals daily — affinity, context, cross-platform behaviour, and more — and the Senior PM for User Store will own the strategy for converting that raw signal into structured, ML-ready user intelligence that is actionable for advertisers at every stage of the funnel. The PM in this role will have end-to-end ownership of a platform that has direct, measurable impact on group revenue.

The Charter

The Senior PM will define and own the strategy for building a unified, enriched, integrated user intelligence layer that drives the roadmap for how raw user signals are structured, enriched, and made consumable by ML & AI systems and advertiser products at scale. This also includes owning the product vision for how internal teams and external advertisers access and act on that intelligence, working closely with ML and engineering to ensure the platform is aligned with real advertiser needs. Central to this role is a single-minded focus on KPI delivery — measuring success through the quality and revenue impact of audiences and intelligence features generated from the user intelligence layer.

The Senior PM needs to understand how to generate and use high-quality user embeddings and latent space representations that are directly consumable by ML models and downstream advertisers. He/ she will work closely with data science and engineering to ensure the enrichment pipeline is production-grade, privacy-compliant, and built for scale.

What You Will Own

• The multi-year product strategy for the Central User Intelligence Spine across InMobi Group.
• The data enrichment and embedding generation roadmap — from raw signals to ML-consumable intelligence.
• Adoption of User Store across internal InMobi products and external advertiser and publisher integrations.
• Strategic data partnerships and sourcing relationships that expand the signal universe.
• Client-facing presence — representing User Store capabilities in advertiser and DSP conversations independently.
• The AI-native user studio product — vision, roadmap, and go-to-market with internal and external stakeholders.

What We Are Looking For

We are looking for a rare profile: someone with the PM craft to drive strategy and adoption, the data intuition of a seasoned practitioner, and the AI fluency to have a genuine opinion on how embeddings are built and consumed — not just talk about them.

Non-Negotiables

• AI-native mindset — Deep familiarity with how AI and ML systems are actually built. You understand how embeddings are generated, what they represent, and how downstream systems consume them. This role will not be a good fit without this foundation.
• End-to-end ownership — You drive things to completion. You are rigorous, deeply accountable, and do not let initiatives stall between strategy and execution.
• Impact-first prioritisation — You have a strong instinct for what moves the needle and the discipline to say no to everything else.
• Engineer or data scientist at heart — You think in systems and are comfortable going deep in technical discussions. A formal background in engineering or data science is not mandatory but is a strong bonus.
• [Bonus Points] Data platform experience — You have built or owned intelligence stores, data pipelines, or recommendation systems at scale. You think in terms of exposing intelligence, not raw data.

Strong Differentiators

• Experience encoding user behaviour into structured, learnable representations for ML systems — embeddings, vector spaces, affinity graphs, or adaptive learning systems.
• Background in CDP (Customer Data Platforms), user store systems, or large-scale data infrastructure products.
• Familiarity with privacy-preserving architectures: clean rooms, differential privacy, or data governance in regulated environments.
• Experience with recommendation systems — understanding what users like and dislike and translating that into product decisions.
• Comfortable with hands-on data deep-dives: able to look at data cuts quickly, visualise hypotheses, and challenge assumptions in technical discussions.
• Prior experience in ad tech, DSP, or publisher ecosystems is a plus, though not a requirement — strong candidates from adjacent industries such as recommendation systems, data platforms, or consumer tech are encouraged to apply.

Core PM Fundamentals

• 5+ years of product management experience with a track record of shipping complex, cross-functional products.
• Ability to translate ambiguous, long-horizon strategy into a clear roadmap with measurable milestones.
• Strong cross-functional leadership — able to align data science, engineering, and commercial teams without direct authority.
• Executive-level communication: able to represent User Store in leadership reviews and client meetings independently.

Why This Role

• One of the most strategically significant product charters within InMobi Group — the intelligence layer that powers the broader platform.
• Direct, measurable impact on group revenue across the advertiser funnel.
• End-to-end ownership from data strategy to ML interfaces to advertiser-facing products — one of the broadest scope PM roles in the organisation.
• High visibility with InMobi Group leadership and external partners.
• An opportunity to work on problems that sit at the frontier of applied AI in mobile advertising.

Why you should join us?

At our core, we believe in the power of data to drive smarter decisions and transform operations. As an Operational Data Scientist, you'll be at the forefront of this mission—leading initiatives that streamline business processes, accelerate time to insight, and align analytics with strategic goals.

You'll work in an environment that values rigor in experimental design, seamless model integration, and impactful operational analytics. We’re not just looking for technical talent—we want a strategic thinker and a collaborative leader who thrives at the intersection of data, business, and execution.

If you're passionate about solving complex problems, influencing high-stakes decisions, and driving measurable outcomes, this is the opportunity to make your mark. Join us and be part of a team that turns data into action—and action into impact.

What will you be doing?

1. Experiment Design and Interpretation:

• Lead and design complex experiments, addressing challenges with statistical rigor.
• Interpret results and provide actionable insights to drive business decisions.

2. Data Engineering Workflow and Design:

• Partner with stakeholders to ensure data systems and structures are efficient and reliable.
• Reduce turnaround time (TAT) for analytics, feature exploration, and experimentation setup

3. Data Science Model Integration:

• Collaborate with data science teams to integrate models into workflows.
• Define success metrics, identify inefficiencies, and leverage model outputs to enhance operations.

4. Proactive and Reactive Analysis:

• Conduct exploratory data analysis, simulations, and hypothesis testing.
• Provide strategic support and actionable insights to address business challenges.

5. Health Metrics Design and Implementation:

• Define, implement, and monitor key performance metrics to assess platform performance and user behavior.

6. Leadership and Collaboration:

• Serve as a liaison between cross-functional teams, advocating for data-driven decisions.
• Mentor analysts and promote a culture of analytics within the organization.

7. Product Impact Tracking:

• Design and implement analyses to monitor product impact.
• Ensure alignment of analytics initiatives with broader business objectives.

What are we looking for?

Skills and Attributes:

• 8–15 years of total professional experience, preferably in Tech, Consulting, or high-scale Analytics organizations.
• 4+ years of people management experience, leading data science, analytics, or operational analytics teams in system-heavy environments.
• Advanced proficiency in SQL and Python — able to drive deep analyses, RCA investigations, and metric instrumentation independently.
• Hands-on experience with Spark or distributed data processing frameworks for scalable analysis.
• Proven ability to design and deploy control systems or feedback loops in collaboration with engineering teams to tune complex algorithms in production.
• Successfully implemented and maintained Data Science models in production, including monitoring and post-deployment tuning.
• Solid foundation in statistical methods, hypothesis testing, and experimental design, especially as applied to system performance and anomaly detection.
• Comfort working with observability and visualization tools — Tableau, Looker, Power BI, or internal metric dashboards like Grafana or Superset.
• Strong record of cross-functional collaboration with engineering, product, SRE, and ML teams to drive system health and platform improvements.
• Demonstrated ability to work through ambiguity, structure diagnostic approaches, and drive data-informed operational decisions.
• Strong strategic and systems thinking mindset — able to reason about interdependent metrics and optimize for system-wide health.

What is the InMobi family like?   

We are an infectious bunch. Be it the way we rise to challenges, the innovative products we create, the dreams we chase or the fun we have at work. We are sure that if you meet us, you will be infected too. Today, we are proud to be the leaders in Mobile advertising and are on an accelerated path of being a leader in enterprise software for marketers. We invite you to free yourself, dream big and chase your passion. We are here today because a few of us did just that.   

What can we promise?   

We offer you an opportunity to work on building enterprise platforms that require you to acquire, hone and demonstrate your ML and AI skills in designing and solving for complex problems, thereby creating software that creates value for our customers in a reliable, scalable, secure, and AI-first manner. At InMobi, you get to work on innovative technologies, work closely with business teams and grow as an overall technology leader.  

Modern work environment, flexible schedule, and smart, creative, down-to-earth people. Internal opportunities to move roles and try out bridge assignments with different teams.  Food for your soul – free meals all days of the week, gym, or yoga class to flex those biceps, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.  

What is the team like?  

At InMobi Enterprise team, we are transforming the way finance, sales, marketing, people, and legal functions operate. We’re driving transformative work across Sales, Marketing, People, and Finance with ML and Agentic AI—and we’re looking for passionate innovators to join us!

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, GenAI and modern agentic AI systems with a strong engineering appetite. You will build and deploy intelligent AI/ML systems that will help transform the business process across the core. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

• Lead the experimentation, design and build of agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Support POCs/ Pilots projects to explore and validate innovative technologies and solutions in ML/AI space.

• Build and operate machine learning models on diverse, high-volume data sources for forecasting, classification and prediction.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Design pipelines for data preparation, model training, evaluation, and deployment in collaboration with engineering counterparts.
• Define best practices for monitoring ML model performance using statistical techniques; identifying drifts, failure modes, and improvement opportunities.
• Contribute to ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
• Document designs, development processes, and best practices to promote knowledge sharing and operational efficiency.

What do we expect from you?

We are seeking candidates with deep expertise in ML and hands-on experience building GenAI and Agentic AI systems.

Skillset: AI/ML Engineering, Python, LLM, RAG, Agentic AI, MCP, REST API

You should have experience with:

• Design, build, and deploy building LLM-powered applications, chatbots, and multi-agent systems to improve efficiency, accuracy, and decision-making.
• Implement and customize GenAI and multi-agent systems using AI frameworks such as LangChain, LangGraph, CrewAI, or similar.
• Create, refine, and maintain prompt templates, chains, and workflows.
• Integrate vector databases (MilvusDB, FAISS, Pinecone, Chroma, etc.) for semantic search and memory.
• Classical ML and deep learning techniques across NLP, clustering, and time series.
• Proficient in deploying ML workflows/models in production system. Continuous monitoring, evaluation, and retraining of models to ensure sustained performance. Ensuring model explainability, accuracy, compliance.
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Stay updated with emerging AI/ML technologies and recommend relevant innovations for the finance domain.
• Drive in design reviews, sprint planning, and technical discussions.
• Collaborating effectively with diverse stakeholders, including technical teams and business leaders.
• Adapting to fast-paced environments and evolving priorities with high energy and autonomy.

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

 Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 8+ years of industry experience in ML/Data Science, with deep proficiency in Python and one or more frameworks: PyTorch, TensorFlow, Scikit-learn.
• Solid understanding of ML fundamentals, regression, tree-based models, clustering, and time series.
• Hands-on experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Experience building Agentic frameworks such as LangGraph, AutoGen, CrewAI, n8n or ReACT-style agents.
• Expertise with algorithms in NLP, Time Series, and Deep Learning, applied on real-world datasets.
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Experience with Model Context Protocols (MCPs) — building or integrating MCP tools, servers, or capabilities.
• Comfortable working in cross-functional teams.
• Strong problem-solving and analytical skills with the ability to work in agile environments.
• Good understanding of data pipelines, APIs, and cloud platforms (Azure/GCP/AWS).
• Excellent communication skills with the ability to simplify complex technical concepts.

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

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:

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

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. 

Job Overview:

Our team is responsible for ensuring that AI systems deployed at scale are measurable, trustworthy, and decision‑ready. We build rigorous evaluation frameworks, analytics platforms, and KPI audits that directly influence product direction and real‑world safety outcomes. This role is primarily evaluation and analytics driven. As a Staff Data Scientist will own the definition, execution, and evolution of evaluation frameworks, metrics, and analytical methodologies used to assess AI/ML feature performance in real‑world deployments. Rather than focusing on core model development, this role emphasizes measurement rigor, error analysis, experimentation, and decision support—ensuring that metrics accurately reflect system behavior, business impact, and safety outcomes.

Key Responsibilities:​

Evaluation & Measurement Ownership

• Design, implement, and maintain offline and online evaluation frameworks for AI/ML features.
• Define, validate, and evolve KPIs, success metrics, and audit methodologies used across teams.
• Perform deep error analysis, bias analysis, and segmentation to identify failure modes and improvement opportunities.
• Own golden datasets, validation protocols, and benchmarking standards.

Analytics & Insight Generation

• Conduct large‑scale analytical studies to understand feature performance, data quality issues, and system behavior.
• Translate complex analytical findings into clear, actionable insights for engineering, product, and leadership stakeholders.
• Challenge existing metrics or evaluation approaches when they fail to capture ground reality.

Experimentation & Statistical Rigor

• Design and review experiments including offline evaluations, controlled rollouts, and A/B tests.
• Ensure statistical correctness in analysis, including bias, variance, confidence intervals, and significance.
• Perform post‑deployment monitoring and regression detection.

Tooling, Automation & Scale

• Build and maintain tools, dashboards, and automation frameworks to scale audits, evaluations, and reporting.
• Improve repeatability, reproducibility, and reliability of analytics pipelines.
• Enable self‑serve analytics and standardized reporting for broader teams.

Leadership & Ownership

• Independently identify gaps in evaluation, metrics, or data quality and drive solutions end‑to‑
• Mentor junior data scientists on statistical rigor, experiment design, and analytical storytelling.

Mandatory Skills:​

• Tech, M.Tech, or PhD in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field.
• 5+ years of experience in data science, analytics, or a closely related domain.
• Strong foundation in probability, statistics, and estimation theory.
• Strong analytical and problem‑solving skills with keen attention to detail.
• Strong programming skills in Python, with solid fundamentals in OOP, algorithms, and data structures.
• Deep familiarity with SQL, complex query writing, indexing, and database internals; working knowledge of at least one NoSQL data store.
• Experience with data visualization and analytical storytelling.
• Excellent written and verbal communication skills.
• Familiarity with AI‑powered tools for analytics and software development, including:
  • Using AI tools for exploratory data analysis, feature ideation, experiment analysis, and documentation.
  • Leveraging AI assistance for rapid prototyping, code refactoring, debugging, and analytical workflows.
  • Ability to critically evaluate AI‑generated outputs for correctness, statistical validity, reproducibility, and production readiness.

 Preferred Skills:​

• Exposure to cloud platforms and services (e.g., AWS Kinesis, EKS, autoscaling systems).
• Experience building lightweight web or service components using Python frameworks (e.g., Flask, Django).
• Prior experience working with large‑scale, noisy, real‑world datasets

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 

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, large-scale recommendation systems, and modern agentic AI systems.

You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

Classical ML & Recommendation Systems

• Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
• Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
• Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.

Agentic Systems & Next-Gen AI

• Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.   
 
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and roposo.com

What should you know about joining Glance?  

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!

What You’ll Do

As a Data Scientist – Recommendation Systems, you will own and drive high-impact ML systems powering personalization across Glance products.

• Design, build, and deploy large-scale recommendation and personalization models using diverse, high-volume data sources.
• Lead rapid experimentation—from hypothesis formulation to offline evaluation and online A/B testing—balancing speed, rigor, and business impact.
• Develop and productionize end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and monitoring.
• Partner closely with Product, Engineering, Design, UX, and Business teams to translate product goals into scalable ML solutions.
• Monitor model health and performance, applying statistical techniques to ensure robustness and long-term effectiveness.
• Explore and prototype new ML techniques to improve relevance, engagement, and monetization.
• Act as a technical interface for stakeholders, clearly articulating trade-offs, results, and next steps.
• Contribute to Glance’s thought leadership through blogs, case studies, and industry conference talks.

What We’re Looking For

Core Expectations

• Deep expertise in Machine Learning, Data Science, and Recommendation Systems at scale.
• Strong applied understanding of experimentation, metrics, and causal reasoning in real-world systems.
• Ability to take models from idea → prototype → production → business impact.

Experience & Skills

• 10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems.
• Hands-on experience applying techniques from ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics.
• Strong programming skills in Python with production-quality code practices.
• Experience with big data ecosystems, especially Apache Spark.
• Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure.
• Experience operating in identity-constrained / privacy-aware environments (e.g., iOS/Android, identity-less systems) is a plus.
• Excellent communication skills—able to explain complex technical ideas clearly to non-technical stakeholders.
• High curiosity, strong problem-solving ability, and a bias toward learning and experimentation.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Economics, Analytics, or Data Science.
• PhD is a plus, but not mandatory.
• We value diverse academic backgrounds—great data scientists come from many disciplines.

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, large-scale recommendation systems, and modern agentic AI systems.

You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

Classical ML & Recommendation Systems

• Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
• Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
• Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.

Agentic Systems & Next-Gen AI

• Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.

Cross-functional impact

• Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance’s consumer experiences.
• Contribute to Glance’s ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.

The experience we need

We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.

You should have experience with:

• Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
• Classical ML and deep learning techniques across NLP, sequence modeling, RL, clustering, and time series.
• Experience in deploying ML workflows/models in production system
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
• Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
• Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Comfortable working in cross-functional teams.
• Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
• Excellent communication skills with the ability to simplify complex technical concepts.

Who we are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools - reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. We’ve grown rapidly in Nigeria and the UK, and we’re now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets - solving real, meaningful problems at scale.

We onboard over a million new customers each month, process hundreds of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our India team is a core part of this scale, with ~100 teammates based across Bengaluru, Mumbai, Pune, Chennai, Hyderabad, and Gurgaon. You’ll work in a fast-paced, high-impact environment alongside experienced operators from companies such as Gojek, Tide, Amazon, Walmart, Paytm, BharatPe, Zeta, Delivery Hero, Grab, and Groupon. If you want to build at scale, work with one of Africa’s highest-volume fintech data sets, and ship products that materially impact tens of millions of users, this is an exceptional time to join.

About the role: 

We’re looking for a hands-on Senior Data Scientist (Fraud) to help detect, prevent, and reduce fraud across one of the largest financial transaction ecosystems in Africa. Operating at the heart of real-time payments, identity, behavioural risk, and transaction monitoring, this role works at massive scale with direct, real-world impact.

You’ll partner closely with Fraud, Risk, Product, and Engineering teams to design, build, and deploy production fraud models that sit directly in decision flows. Sitting at the intersection of data science, fraud strategy, and product, you’ll translate complex behavioural signals into high-confidence, real-time decisions - balancing fraud loss, customer experience, and regulatory expectations to protect millions of customers and businesses.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What You’ll Do

• Develop and deploy fraud detection, transaction monitoring, and behavioural risk models across payments, accounts, onboarding, and merchant activity
• Design and run experiments to optimise fraud catch rates, false positives, and customer friction
• Partner with product and engineering teams to embed models into real-time decisioning systems
• Build features from high-volume transactional, device, network, and behavioural data
• Continuously monitor model performance, drift, and emerging fraud patterns
• Ensure data quality, governance, and responsible use of models in regulated environments
• Support investigations, strategy, and policy teams with advanced fraud analytics
• Mentor analysts and product teams on experimentation, detection strategy, and data-driven decision making

We would love to hear from you if…

• A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar)
• 5+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime
• Hands-on experience with fraud detection, transaction monitoring, or behavioural risk modelling
• Proficiency in SQL and at least one modelling/programming language (Python or R)
• Experience with machine learning, anomaly detection, network/graph features, and real-time decision systems
• Strong intuition for fraud typologies, adversarial behaviour, and evolving attack patterns
• Ability to translate complex analysis into clear, actionable recommendations for technical and non-technical stakeholders
• High ownership mindset and comfort working in fast-paced, cross-functional product environments

What we can offer you

• Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
• Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
• Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits

What to expect in the hiring process

• A preliminary phone call with the recruiter
• A coding exercise on HackerRank – covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
• A take-home assignment
• A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
• A behavioural and technical interview with the hiring manager

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

Who we are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools - reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. We’ve grown rapidly in Nigeria and the UK, and we’re now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets - solving real, meaningful problems at scale.

We onboard over a million new customers each month, process hundreds of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our India team is a core part of this scale, with ~100 teammates based across Bengaluru, Mumbai, Pune, Chennai, Hyderabad, and Gurgaon. You’ll work in a fast-paced, high-impact environment alongside experienced operators from companies such as Gojek, Tide, Amazon, Walmart, Paytm, BharatPe, Zeta, Delivery Hero, Grab, and Groupon. If you want to build at scale, work with one of Africa’s highest-volume fintech data sets, and ship products that materially impact tens of millions of users, this is an exceptional time to join.

About the role: 

At Moniepoint, data is at the core of everything we do. We are a customer-centric company, and your work will enable our teams to make informed, data-driven decisions that directly impact the success of our business. We are seeking a data-driven, impact-oriented Senior Data Scientist to power Moniepoint’s consumer lending decisions at scale. You will build the models, experiments, and insights that shape how we acquire, underwrite, and retain millions of customers across Nigeria and Africa.

This role is pivotal in driving our pricing, credit limit modelling, and credit model deployment strategy in a growing business with unparalleled opportunities to give access to millions of customers. You’ll collaborate with our amazing Consumer Credit team and drive how we think about risk ranking, product offering, and data infrastructure to create the best personalised offers for our customers. You’ll be responsible for building our first suite of credit risk models and help drive a culture of how we should think about machine learning vs more traditional methods - bringing fresh thinking to inspire both the team and our customers.

Sitting at the intersection of data science, credit risk, and product, you’ll translate complex data into actionable decisions that drive growth with healthy portfolio performance.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What You’ll Do

• Develop and deploy credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
• Design and run experiments to optimise approval rates, loss rates, and profitability
• Partner with product squads to embed decision logic into real-time systems
• Ensure data quality, compliance, and ethical use of models across all decisioning processes
• Mentor product squads on best practices in experimentation and data-driven decision making
• Provide models to optimise outcomes in collections, churn management and user retention

We would love to hear from you if…

• You’re comfortable with Statistics - and have a Degree or qualifications  in a quantitative field (Statistics, Mathematics, Engineering or similar)
• You have +5 years of experience in data science, decision science, or risk analytics within financial services
• Working knowledge of credit risk, consumer lending, and regulatory considerations
• Proficiency in SQL and at least one modelling/programming language (Python, R)
• Experience with A/B testing, machine learning, collections modelling and churn management
• Ability to translate complex analyses into clear recommendations for business stakeholders
• High ownership mindset and comfort working in fast-paced, cross-functional teams

What we can offer you

• Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
• Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
• Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits

What to expect in the hiring process

• A preliminary phone call with the recruiter
• A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
• A take-home assignment
• A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
• A behavioural and technical interview with the hiring manager

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

About Tekion

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform. Our Automotive Retail Cloud (ARC), Automotive Enterprise Cloud (AEC), and Automotive Partner Cloud (APC) connect OEMs, retailers, and consumers through one seamless platform. Utilizing cutting-edge technology, big data, machine learning, and AI, Tekion is transforming the automotive retail ecosystem. We're inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it with offices in North America, Asia, and Europe, Tekion employs around 3,000 people worldwide.

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.

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

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

We're looking for a dynamic Senior Data Scientist to join our team, working alongside our founders, financial analysts, product managers, and engineers. This is your chance to get hands-on with massive datasets, crafting the metrics that matter to institutional investors worldwide. For those who are curious and passionate about financial technologies, this is a great opportunity to work at an extremely well-capitalized startup with a proven team of senior financial and tech industry talent to build the future of investing tools.

Responsibilities:

• Work with large and complex data sets and derive investment-relevant metrics in close partnership with financial analysts and engineers.
• Apply knowledge of statistics, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to the development of fundamental metrics needed to evaluate various assets.
• Implement the risk factor model using advanced statistical and programming techniques, ensuring its performance aligns with the proposed design.
• Conduct rigorous testing and validation of the model to ensure its effectiveness in identifying, quantifying, and managing various risk factors.
• Build customer-facing metrics and dashboards.
• Work closely with analysts, engineers, and Product Managers and provide feedback as we develop our data analytics and research platform.

Requirements:

• Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience (or) degree in an analytical field (e. g. Computer Science, Engineering, Mathematics, Statistics, Operations Research, Management Science). IIT preferred.
• 3+ years of experience with data analysis and metrics development.
• 3+ years of experience analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across stakeholders.
• 2+ years of experience writing SQL queries.
• 2+ years of experience scripting in Python.
• Interested in learning new technologies to solve customer needs with lots of creative freedom.
• Strong communication skills and business acumen.
• Self-starter, motivated by an interest in developing the best possible solutions to problems.
• Strong SQL and Python programming skills.
• Experience with Airflow, Google BigQuery, and Clickhouse is a plus.