O que a vaga pede
- Model adaptation: Develop/Take models developed by the team — including causal-informed models from the causal inference-focused Data Scientist — and adapt them to different business cases across the program.
- Experimentation & iteration: Design, run, and interpret A/B tests, and adjust or retrain models based on test results and incoming data, closing the loop between experimentation and model improvement.
- Deployment: Validate models from prototype to production deployment on Databricks and Azure.
- Monitoring: Own ongoing performance monitoring of deployed models — drift detection, retraining triggers, and alerting when performance degrades.
- Collaboration: Work closely with the Senior Data Engineer (data foundation), the Analytics Engineer (BI and insight layer), and the causal inference-focused Data Scientist — turning their work into deployed, monitored, business-adapted models. Requirements — Must Have
- Experience: 6+ years of hands-on, professional experience in data science / machine learning — production work, not academic-only.
- ML & Statistics: Proven track record building, deploying, and monitoring machine learning and statistical models in production, with strong command of A/B testing methodology and experimentation design.
- Causal inference: Working knowledge of causal models and causal ML — enough to understand, adapt, and build on causal-informed models produced by a specialist teammate. Deep original causal-inference research is not the primary bar for this role.
- Stack: Databricks, PySpark, Python, Azure.
- Academic background: Strong foundation in a quantitative field — Mathematics, Statistics, Computer Science, or related — required; an advanced degree (MSc/PhD) is a plus but not required for this more applied role.
- English: Fluent English is required — this role works directly with a global program team.
- Business acumen: Comfortable adapting models to different business cases and framing technical trade-offs in terms of business impact for non-technical stakeholders. Soft Skills