Manager, Data Science

📋 Description

• Own end-to-end data science projects from problem to delivery.
• Lead projects and drive technical decisions with minimal supervision.
• Scale delivery by leading a data science team and setting standards.
• Design, build, and review ML models (regression, NLP, LLMs).
• Lead Marketing Mix Modelling (MMM) using Meridian, Robyn, PyMC.
• Guide marketing analytics: attribution, spend optimization, CLTV.

🎯 Requirements

• Python programming (4–6y): pandas, NumPy, scikit-learn; basics of TF/PyTorch.
• ML & LLMs (4–6y): core ML, simple DL, applied LLM use.
• SQL & Data Warehousing (4–5y): BigQuery/Snowflake/Redshift.
• MLOps & CI/CD (3–4y): Docker, Kubernetes basics, MLflow, Airflow.
• Cloud Platforms (3–4y): GCP, AWS, Azure.
• Marketing Analytics & MMM (4–6y): MMM, attribution, spend optimization.