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

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.

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

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 

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.

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

Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About Us

The Agents team at Google DeepMind India is driven by the mission of developing foundational capabilities in Large Models towards realizing AGI. We focus on uncovering emergent agentic behaviors through novel reinforcement learning algorithms run at scale.  

We also apply our research advances to Gemini and critical product launches in Google, touching the lives of hundreds of millions of users, and we are looking forward to doing more!

We are seeking a highly motivated and innovative Research Scientist to join our team in Bangalore, focused on advancing the state-of-the-art in autonomous agents  through reinforcement learning and ML optimization methods. You will conduct cutting-edge research on large language models (LLMs), focusing on the development of more capable, robust autonomous agents.

The Role

Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic architecture towards the end goal of solving and building Artificial General Intelligence.

Having pioneered research in the world's leading academic and industrial labs in PhDs, post-docs or professorships, Research Scientists join Google DeepMind to work collaboratively within and across Research fields. They develop solutions to fundamental questions in machine learning and AI.

Key responsibilities:

• Design, implement and evaluate models, agents and software prototypes of large foundational models.
• Push the boundary of state of the art RL methods and machine learning optimization methods to build autonomous agents. 
• Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet ambitious research goals.
• Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
• Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About You

You are a passionate and talented researcher with a strong foundation and a proven ability to conduct impactful research in AI. You embrace change and thrive under ambiguity. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious research challenges. You are passionate about seeing your research translated into real-world products that improve the lives of users and are eager to work in an environment where research has a direct path to product impact.  You are eager to see your research contribute to real-world applications and are driven by a desire to create positive change through AI.

• PhD in Computer Science, Artificial Intelligence, or a related field.
• Strong publication record in top-tier machine learning conferences or journals.
• Solid understanding of deep learning, natural language processing, computer vision, and/or speech processing.
• Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.

In addition, the following would be an advantage: 

• Experience with multimodal learning, large language models, and/or assistive AI agents.
• Experience with prompt engineering, few-shot learning, post-training techniques, and evaluations.
• Familiarity with large-scale model training and deployment.
• Strong programming skills in Python or similar languages.
• Excellent communication and collaboration skills.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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.