ML Data Science Engineer

The ML/Data Science Engineer will support elastic data science and machine learning work for a modern Snowflake and Databricks-based data platform. The role involves supporting data science workflows using Databricks, Snowflake, Python, and SQL, preparing datasets for ML, enrichment, analytics, and product features, and assisting with feature engineering, model evaluation, and data validation. The successful candidate will engage closely with business stakeholders to translate analytical requirements into robust, production-ready data solutions that support long-term organizational growth. This position also involves supporting knowledge-sharing sessions, contributing to internal best-practice documentation, and helping to build a culture of continuous learning within the data science team.

3-8 years of experience with Databricks, Snowflake, Python, and SQL for data science workflows. Experience in preparing datasets for ML, feature engineering, model evaluation, and data validation. Any Graduate qualification. The ideal candidate will bring a proactive, solutions-oriented approach, strong organizational skills, and a commitment to delivering high-quality outcomes within agreed timelines. A strong customer-first attitude and willingness to travel to client locations as needed will be an added advantage for this role. Familiarity with change management practices and a track record of successful stakeholder engagement across diverse business units is preferred.