Data Scientist

Ford - Lincoln Veteran Careers Program; Chennai; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Ford in Chennai, India seeks a senior data scientist to design, deploy end-to-end analytics, ML, and GenAI solutions. You will balance classical modeling with modern LLM architectures to create measurable business value.

Responsibilities include building scalable pipelines, NLP/LLM tasks, RAG pipelines, and collaborating with IT to deploy on cloud; strong Python and ML library experience required.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field.
• Strong hands-on experience in Python for data analysis and AI development.
• Experience with ML libraries like NumPy, Pandas, scikit-learn, TensorFlow, PyTorch.
• Experience with SQL and large-scale datasets.
• 5+ years of experience applying ML and AI techniques.
• Strong experience with Generative AI, LLMs, NLP, and RAG architectures.
• Experience with cloud platforms, especially Google Cloud Platform (GCP) including Vertex AI and BigQuery.
• Experience with NoSQL and Hadoop ecosystem.
• Proficiency with Git and collaborative development.

Responsibilities

• Translate business objectives into analytical and mathematical problem statements.
• Design, implement, train, tune, validate, and monitor predictive and prescriptive models.
• Apply ML techniques: regression, classification, clustering, ensembles, deep learning, time-series.
• Analyze large, high-dimensional datasets to identify patterns and trends.
• Develop scalable analytics pipelines and reusable modelling frameworks.
• Design and implement Generative AI and LLM-based solutions (NLP, NLG, semantic search).
• Build and deploy Retrieval Augmented Generation (RAG) pipelines for enterprise data.
• Fine-tune, evaluate, and monitor Large Language Models for business applications.
• Apply text preprocessing, tokenization, embedding generation, prompt engineering, and LLM orchestration techniques.
• Leverage GenAI frameworks to build scalable AI applications.
• Build end-to-end system designs covering data ingestion, feature engineering, modeling, inference, and outputs.
• Partner with IT to deploy analytics on cloud infrastructure.
• Communicate insights and recommendations to stakeholders.
• Explore new data sources and tools to enhance capabilities.
• Package findings into documentation, dashboards, and executive presentations.

Skills

Python

NumPy

Pandas

scikit-learn

TensorFlow

PyTorch

Git

NLP

LLMs

RAG

Education

Bachelor’s or Master’s degree in Data Science/CS/Engineering

Master’s or Ph.D. in quantitative/engineering

Tools

Transformers

LangChain

Vertex AI

BigQuery

NoSQL

Hadoop

Job description

You will design, develop, and deployend-to-end analytics, machine learning, and GenAI solutions, working with large-scale structured and unstructured data. The role balancesclassical ML and statistical modelingwithmodern LLM-based architectures, ensuring both approaches are applied where they create the most value.

• Translate business objectives into well-defined analytical and mathematical problem statements
• Design, implement, train, tune, validate, and monitor predictive and prescriptive models
• Apply machine learning techniques such as regression, classification, clustering, ensemble methods, deep learning, and time-series analysis
• Analyze large, high-dimensional datasets to identify patterns, drivers, anomalies, and trends
• Develop scalable analytics pipelines and reusable modelling frameworks suitable for automation and production deployment
• Design and implementGenerative AI and LLM-based solutions, including NLP, NLG, and semantic search
• Build and deployRetrieval Augmented Generation (RAG)pipelines for enterprise knowledge and data extraction use cases
• Fine-tune, evaluate, and monitor Large Language Models for business applications
• Apply text preprocessing, tokenization, embedding generation, prompt engineering, and LLM orchestration techniques
• Leverage modern GenAI frameworks and libraries (e.g., Transformers, LangChain-based workflows) to build scalable AI applications.

• Build end-to-end system designs covering data ingestion, feature engineering, modeling, inference, and user-facing outputs
• Partner with IT and platform teams to deploy analytics and AI solutions on cloud infrastructure
• Work with cross-functional stakeholders to communicate insights, model results, and recommendations clearly
• Explore new data sources, tools, and technologies to continuously enhance analytics and AI capabilities
• Package findings into clear documentation, dashboards, and executive-level presentations

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, Applied Mathematics, Operations Research, or related quantitative field
• Strong hands-on experience inPythonfor data analysis, machine learning, and AI development
• Experience with common ML and analytics libraries (e.g., NumPy, Pandas, scikit-learn, TensorFlow, PyTorch)
• Experience with SQL and working with relational and large-scale datasets
• Experience building analytical models and communicating insights to business stakeholders
• Master’s or Ph.D. in a quantitative or engineering discipline
• 5+ years of experience applying machine learning, advanced analytics, and AI techniques in real-world settings
• Strong experience withGenerative AI, LLMs, NLP, and RAG architectures
• Experience with cloud platforms, especiallyGoogle Cloud Platform (GCP), including Vertex AI, BigQuery, and related services
• Experience working with large-scale data ecosystems (e.g., NoSQL databases, Hadoop ecosystem)
• Proficiency with version control (Git) and collaborative development practices
• Strong mathematical foundations in probability, linear algebra, optimization, and numerical methods
• Excellent problem-solving, communication, and data storytelling skills
• Ability to work independently while collaborating effectively with cross-functional teams

Comfortable operating in fast-paced, ambiguous, and evolving problem spaces.