
Product Data Scientist
1 week ago
What You'll Do
- Model Intelligence into Product: Build and deploy machine learning models that tackle critical product problems — from recommendation engines and segmentation models to churn predictors — and partner with ML Engineers to bring them to production.
- Advance Product Understanding: Apply causal inference methods and advanced experimental design to evaluate product initiatives, ensuring every decision is grounded in robust data.
- Own Data Infrastructure: Develop scalable data models and pipelines that fuel analytics, experimentation, and personalization at scale.
- Collaborate at Speed: Work hand-in-hand with cross-functional stakeholders to translate evolving business needs into actionable data science solutions.
- Influence Roadmaps with Insight: Provide clear, data-backed product insights and uncover opportunities that drive user engagement and retention.
- Understand & Predict Behavior: Build behavioral models that power adaptive user experiences and surface key signals for product teams.
- Advanced degree (MSc/PhD) in a quantitative field like Data Science, Computer Science, Statistics, or Applied Math.
- 3 years of experience in a fast-paced, product-focused data science role.
- Expertise in at least one of the following: recommendation systems, causal inference (e.g., uplift modeling), segmentation, or churn prediction.
- Strong knowledge of experimental methods (A/B tests, quasi-experiments) and causal inference.
- Proficiency in Python and libraries such as pandas, scikit-learn, PyTorch, TensorFlow, or XGBoost.
- Skilled in SQL and data wrangling across large datasets.
- Experience with cloud-based data platforms (AWS, GCP, or Azure).
- Excellent communication skills — able to influence non-technical stakeholders and translate findings into action.
- A bias toward action: comfortable building in ambiguity and learning on the fly.
High Pace. High Growth. Real Impact.
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