Role & responsibilities

- Translate product and customer problems into well-defined analytics and ML use cases.

- Perform data exploration, feature engineering, statistical analysis and experimentation.

- Develop, train, validate and optimize machine learning and predictive models.

- Define appropriate model performance metrics, benchmarks and acceptance criteria.

- Convert prototypes and experiments into scalable, production-ready capabilities.

- Work with Product, Architecture and Engineering teams to integrate models and analytics into SaaS products and platforms.

Model Evaluation & Productization

- Evaluate models and analytical solutions developed by internal teams, technology partners and specialist solution providers.

- Assess model assumptions, data requirements, accuracy, robustness, explainability and limitations.

- Benchmark alternative models/approaches and provide evidence-based recommendations.

- Establish practices for model versioning, validation, monitoring,



drift detection and continuous improvement.

- Ensure that externally sourced models can be effectively integrated, governed and evolved within the product.

Preferred candidate profile

- 5-8 years of relevant experience in Data Science, Machine Learning, Applied Analytics or related roles.

- Experience building ML/analytics capabilities that have been deployed into production products or platforms.

- Experience working with automotive, mobility, connected vehicle, battery/EV, IoT or industrial datasets is desirable but not mandatory.

- Experience collaborating with technology partners, research organizations or academic institutions is an advantage.

- Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative discipline preferred.

📌 Data Scientist Machine Learning & Applied Analytics. (Bengaluru)
🏢 Tata Elxsi
📍 Bengaluru