Sr Data Scientist
Senior Data Scientist at Birlasoft in Pune: builds and deploys ML/AI models end to end, from advanced statistical analysis and predictive modeling to full ML pipelines and MLOps frameworks for CI/CD, monitoring, and model governance. Core stack is Python, with Databricks Mosaic AI and Snowflake Cortex as pluses.
- Compensation
- Not disclosed
- Location
- Pune, IN
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Strong expertise in AI, Machine Learning, and MLOps
- Deep understanding of statistical modeling, predictive analytics, and Python-based data ecosystems
- Experience building end-to-end ML pipelines: data ingestion, feature engineering, training, validation, deployment
Nice to have
- Exposure to modern platforms such as Databricks Mosaic AI and Snowflake Cortex
Full description
Area(s) of responsibility
Role Overview
We are seeking a highly skilled Data Scientist with strong expertise in Artificial Intelligence (AI), Machine Learning (ML), and MLOps. The ideal candidate will be responsible for building scalable predictive models, driving advanced analytics, and operationalizing ML models in production environments. This role requires a deep understanding of statistical modeling, predictive analytics, and Python-based data ecosystems, with exposure to modern platforms such as Databricks Mosaic AI and Snowflake Cortex being an added advantage.
Key Responsibilities
- Design, develop, and deploy machine learning and AI models for real-world business problems.
- Perform advanced statistical analysis and build predictive models to derive actionable insights.
- Develop and implement end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and deployment.
- Build and manage MLOps frameworks for continuous integration, delivery, monitoring, and model governance.
- Work closely with data engineering teams to ensure robust and scalable data pipelines.
- Conduct exploratory data analysis (EDA) and hypothesis testing to support data-driven decision-making.