Data Scientist
Ford Motor Company (company site, opens in a new tab)4+ yrsChennaiHybridDirect career pageEst. 15–30 LPA
Posted on 15 Sept
Reach people at Ford Motor Company
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Ford Motor Company you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Collaborate with business stakeholders to translate complex challenges into scalable data science and Generative AI solutions.
- Design, build, validate, and deploy machine learning models and autonomous AI agent systems leveraging frameworks like Google ADK, LangGraph, LangChain.
- Manage end-to-end model lifecycle including data preparation, feature engineering, deployment, monitoring, and optimization ensuring data quality and responsible AI practices.
Minimum Requirements
- Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or related quantitative field.
- Minimum 4 years hands-on experience in machine learning techniques (regression, classification, clustering, decision trees, random forests, SVMs).
- 4+ years of Python programming experience using libraries such as Pandas, NumPy, Matplotlib, Seaborn, plus 4+ years SQL experience.
- At least 2 years experience developing Generative AI applications with prompt engineering, RAG, embeddings, or model fine-tuning; experience with AI agent frameworks like Google ADK, LangGraph, or LangChain.
Ideal Candidate Profile
- Experienced individual contributor capable of independently delivering end-to-end data science and Generative AI solutions within business contexts.
- Strong technical expertise with advanced skills in both classical machine learning and Generative AI technologies, including agentic workflows.
- Comfortable working cross-functionally to interpret business problems into technical solutions and communicate findings effectively to technical and non-technical audiences.