Job Category: Enterprise Technology

Degree Level: Master's Degree or equivalent

Job Description:

You will design, develop, and deploy end-to-end analytics, machine learning, and GenAI solutions, working with large-scale structured and unstructured data. The role balances classical ML and statistical modeling with modern 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 implement Generative AI and LLM-based solutions, including NLP, NLG, and semantic search
- Build and deploy Retrieval 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.

Responsibilities:

- 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

Qualifications:

- 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 in Python for 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 with Generative AI, LLMs, NLP, and RAG architectures
- Experience with cloud platforms, especially Google 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 rapid-paced, ambiguous, and evolving problem spaces.

📌 Data Scientist (Chennai)
🏢 Ford
📍 Chennai