Data Science Specialist

We are looking for a highly skilled Data Science Specialist to help turn our predictive/analytics tools into a trusted decision platform for Content/Programming, CRM/Marketing, and Product by building repeatable analytics and ML modules: lifecycle segmentation, churn risk, taste communities, and measurement of CRM interventions. This position will also support the handover and improvement of existing work and ensure it becomes operational, monitored, and improved over time.

Responsibilities:

• Implement new decision pages and reusable metrics;
• Add analysis angles from the existing backlog;
• Translate analytics into action outputs;
• Operationalize lifecycle segments/personas/churn outputs: automated refresh, drift checks, and QA;
• Improve the existing churn model and upgrade personas;
• Partner with CRM/Marketing on measurement of interventions (email campaigns, triggered messages);
• Build a practical evaluation framework: holdouts, A/B test design support, uplift, etc.
• Write production-friendly SQL;
• Help define data contracts for key marts used by tools and models.

Skills:

• Solid ML foundations: classification, clustering, validation, leakage prevention, feature engineering;
• Strong Python (pandas, numpy), clean coding practices, and ability to ship maintainable notebooks/scripts (GIT);
• Strong SQL (joins, window functions, incremental logic; comfortable reading complex transformations);
• Comfortable with product analytics and causal thinking basics (A/B tests, cohorts, retention curves);
• Ability to explain results to non-technical stakeholders.

Nice to have:

• Familiarity with recommendation systems evaluation (top‑N metrics, coverage/diversity, cold-start);
• Exposure to Cloud Data Lake (Bigquery, Databricks, Snowflake), dbt, Airflow concepts (even if not deep);
• Streamlit / dashboard building or strong SW development experience;
• Any experience with embeddings/metadata or vector similarity is a plus.

Date the job becomes available: March 1, 2026