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MT2 Data · São Paulo, Brazil

Senior Data Scientist

seniorfull timePosted 6 days ago
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Stack mentioned

databricksazurestatisticspythondata-sciencea/b-testingdata-engineeringmachine-learningapache-spark

MT2 Data is looking for a Senior Data Scientist to join a global automotive client program. This role is the applied, production-facing half of the team's data science work: you take models — including causal-informed models and adapt them to different business cases, test and adjust them against A/B testing results and new data, deploy them to production, and own their ongoing performance monitoring.

Key Responsibilities

• 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