Data Scientist

Ford Motor Company

. Partner with business stakeholders to understand challenges, define analytical approaches, and translate business requirements into data science solutions .

Posted 9/15/2026full-timeChennai • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in machine learning techniques, data analysis, and Generative AI solutions, with a strong focus on model development, deployment, and data governance. Proficient in translating business requirements into actionable data science strategies while effectively communicating insights to diverse audiences.

Highest-signal resume keywords

Machine Learning TechniquesPython for Data AnalysisGenerative AI DevelopmentSQL and Relational DatabasesGoogle Cloud Platform (GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

RegressionClassificationClusteringDecision TreesRandom ForestsSupport Vector MachinesData PreparationFeature EngineeringModel TrainingModel Evaluation

Soft Skills

Problem-SolvingCommunicationStakeholder ManagementPresentation Skills

Tools & Technologies

PandasNumPyMatplotlibSeabornGoogle Agent Development Kit (ADK)LangGraphLangChainFAISSPineconeVertex AI Vector Search

Industry Keywords

Data ScienceMachine LearningGenerative AIData GovernanceAnalytics Methodologies

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformNumpyPandasPythonSQL

About the role

Key responsibilities & impact

Partner with business stakeholders to understand challenges, define analytical approaches, and translate business requirements into data science solutions
Analyze structured and unstructured datasets to identify trends, patterns, and actionable insights
Design, build, validate, and deploy machine learning and statistical models to support business decision-making
Develop Generative AI solutions leveraging prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and large language models
Build and deploy autonomous and multi-agent systems using Google Agent Development Kit (ADK), LangGraph, LangChain, or similar orchestration platforms
Design scalable data preparation, feature engineering, and data augmentation pipelines to improve model performance and robustness
Support end-to-end model lifecycle activities, including problem scoping, experimentation, model training, evaluation, deployment, monitoring, and optimisation
Ensure data quality, integrity, governance, and responsible AI practices throughout the analytics lifecycle
Stay informed about emerging developments in machine learning, data science, Generative AI, and analytics methodologies, and apply relevant innovations to business challenges
Communicate analytical findings and recommendations effectively to technical and non-technical audiences

Requirements

What you’ll need

Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or a related quantitative discipline
4+ years of hands-on experience applying machine learning techniques including regression, classification, clustering, decision trees, random forests, and support vector machines
4+ years of experience using Python for data analysis, machine learning, and visualisation, including Pandas, NumPy, Matplotlib, and Seaborn
4+ years of experience in SQL and relational database systems
2+ years of experience developing Generative AI applications using prompt engineering, RAG architectures, embeddings, or model fine-tuning techniques
Experience developing AI agents or agentic workflows using Google ADK, LangGraph, LangChain, or similar frameworks
Familiarity with vector databases and semantic retrieval platforms such as FAISS, Pinecone, Vertex AI Vector Search, or similar technologies
Preferred: Master's degree or PhD in a related quantitative field
Preferred: Experience developing and deploying machine learning solutions on Google Cloud Platform (GCP)
Preferred: Strong understanding of probability, statistical inference, linear algebra, numerical methods, optimisation, and neural network fundamentals
Preferred: Excellent problem-solving, communication, stakeholder management, and presentation skills

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Ford Motor Company Website LinkedIn All Job Openings 10,000+ employees Founded 1903 📦 Logistics 💼 Consulting 📣 Marketing 💰 Post-IPO Debt on 2023-08 Logistics
Consulting
Marketing Ford Motor Company is a globally renowned automotive company based in the United States, established by Henry Ford. The company is committed to building a better world where every individual has the freedom to move and follow their dreams. Ford is dedicated to innovation, with a focus on services, experiences, and software alongside its traditional vehicle manufacturing. The company is actively involved in sustainability initiatives and aims to meet ambitious environmental targets. Ford values service, community impact, and strives to combine business success with social and environmental responsibility. With a rich history of over 121 years, Ford continues to adapt and lead in the evolving automotive landscape. Data Scientist 🔥 1 hour ago 🏢🏡 Chennai – Hybrid ⏰ Full Time 🟡 Mid-level 🟠 Senior 📊 Data Scientist 👻 Ghost score 10% Apply Now Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Partner with business stakeholders to understand challenges, define analytical approaches, and translate business requirements into data science solutions
Analyze structured and unstructured datasets to identify trends, patterns, and actionable insights
Design, build, validate, and deploy machine learning and statistical models to support business decision-making
Develop Generative AI solutions leveraging prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and large language models
Build and deploy autonomous and multi-agent systems using Google Agent Development Kit (ADK), LangGraph, LangChain, or similar orchestration platforms
Design scalable data preparation, feature engineering, and data augmentation pipelines to improve model performance and robustness
Support end-to-end model lifecycle activities, including problem scoping, experimentation, model training, evaluation, deployment, monitoring, and optimisation
Ensure data quality, integrity, governance, and responsible AI practices throughout the analytics lifecycle
Stay informed about emerging developments in machine learning, data science, Generative AI, and analytics methodologies, and apply relevant innovations to business challenges
Communicate analytical findings and recommendations effectively to technical and non-technical audiences 🎯 Requirements
Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or a related quantitative discipline
4+ years of hands-on experience applying machine learning techniques including regression, classification, clustering, decision trees, random forests, and support vector machines
4+ years of experience using Python for data analysis, machine learning, and visualisation, including Pandas, NumPy, Matplotlib, and Seaborn
4+ years of experience in SQL and relational database systems
2+ years of experience developing Generative AI applications using prompt engineering, RAG architectures, embeddings, or model fine-tuning techniques
Experience developing AI agents or agentic workflows using Google ADK, LangGraph, LangChain, or similar frameworks
Familiarity with vector databases and semantic retrieval platforms such as FAISS, Pinecone, Vertex AI Vector Search, or similar technologies
Preferred: Master's degree or PhD in a related quantitative field
Preferred: Experience developing and deploying machine learning solutions on Google Cloud Platform (GCP)
Preferred: Strong understanding of probability, statistical inference, linear algebra, numerical methods, optimisation, and neural network fundamentals
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