Data Science Specialist

Job Description: Offshore ML / Data Science Engineer - Optional Flex Role We are looking for an offshore ML/Data Science Engineer to support elastic data science and machine learning work for a modern Snowflake and Databricks-based data platform. This role is best suited for authorized project work, not baseline KTLO operations. Responsibilities: Support data science workflows using Databricks, Snowflake, Python, and SQL. Help prepare datasets for ML, enrichment, analytics, and product features. Assist with feature engineering, model evaluation, and data validation. Operationalize ML workflows in partnership with data engineering and DevOps. Document assumptions, lineage, outputs, and model/data quality concerns. Required skills: 3+ years in data science, ML engineering, or analytics engineering. Strong Python and SQL. Experience with Databricks notebooks/jobs and Snowflake data. Understanding of data pipelines, model lifecycle, and production data quality. Nice to have: MLflow, Spark, feature stores, Snowflake Cortex/Snowflake Intelligence, LLM/data product experience. Job Description: Offshore ML / Data Science Engineer - Optional Flex Role We are looking for an offshore ML/Data Science Engineer to support elastic data science and machine learning work for a modern Snowflake and Databricks-based data platform. This role is best suited for authorized project work, not baseline KTLO operations. Responsibilities: Support data science workflows using Databricks, Snowflake, Python, and SQL. Help prepare datasets for ML, enrichment, analytics, and product features. Assist with feature engineering, model evaluation, and data validation. Operationalize ML workflows in partnership with data engineering and DevOps. Document assumptions, lineage, outputs, and model/data quality concerns. Required skills: 3+ years in data science, ML engineering, or analytics engineering. Strong Python and SQL. Experience with Databricks notebooks/jobs and Snowflake data. Understanding of data pipelines, model lifecycle, and production data quality. Nice to have: MLflow, Spark, feature stores, Snowflake Cortex/Snowflake Intelligence, LLM/data product experience.