Develop and maintain production data science models for attribution, marketing mix modelling, incrementality testing, and brand impact measurement. Lead projects end to end, select modelling approaches, debug unfamiliar codebases, apply AI tooling, collaborate with QA, communicate technical findings to clients, and mentor junior colleagues. The role requires strong Python, SQL, machine learning, production engineering, stakeholder communication, and independent ownership.

Build and maintain production data engineering pipelines using SQL, dbt, and Python. Contribute to data ingestion, transformation, API-serving workflows, testing, debugging, cloud infrastructure, and AI-assisted engineering. Collaborate with data engineers, analysts, and product stakeholders while learning through mentorship, code reviews, and hands-on early-career training.