About the Role

Own the full data loop: make data clean, fresh, and reliable and ship predictive models that move business KPIs. You’ll design schemas, build APIs and pipelines, create curated datasets and features, and deliver ML that turns data into measurable impact.

Responsibilities

Data Foundations (Data Engineering)

• Design, normalize, and optimize database schemas (PostgreSQL, MySQL, MongoDB) for scalability and reliability.
• Build and monitor ETL/ELT pipelines (Airflow / dbt / Prefect) with clear SLAs/SLOs and data tests.
• Expose data via internal services and RESTful APIs (FastAPI/Flask/Django); integrate third-party APIs.
• Implement observability and data quality checks; ensure security, access control, and compliance.

Intelligence & Impact (Data Science)

• Explore data, frame hypotheses, and define success metrics and baselines.
• Build, validate, and iterate predictive models (scikit-learn / TensorFlow / PyTorch).
• Run experiments/A-B tests; analyze causal impact; translate findings into product decisions.
• Operationalize models (batch or real-time), add monitoring/drift alerts, and close the loop via dashboards.

Collaboration & Reliability

• Partner with product, design, and ops to prioritize impactful features.
• Troubleshoot production issues, optimize performance, and maintain high uptime.
• Stay current on web, analytics, and DevOps best practices.