Senior Data Scientist
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Job Description
Senior Data Scientist driving product analytics, experimentation, and AI measurement for a product-led organization. Building models, metrics, dashboards, and recommendations that guide product roadmap and investment decisions.
Responsibilities:
- Partner with Product Managers, Engineers, and cross-functional stakeholders to answer strategic product questions through reporting, analysis, deep dives, and predictive or prescriptive modeling
- Forecast business outcomes and identify opportunities to improve product performance
- Define, maintain, and improve key product metrics, dashboards, and monitoring frameworks
- Apply machine learning techniques to customer behavior, engagement, retention, churn, propensity scoring, segmentation, recommendation systems, and personalization initiatives
- Evaluate product launches, feature changes, and AI-enabled initiatives against success metrics and communicate recommendations
- Support experimentation and measurement design, including hypothesis development, test readouts, and post-launch evaluations
- Build scalable modeling, reporting, and self-service analytics assets
- Partner with data engineering and platform teams to improve data quality, instrumentation, metric definitions, and reporting pipeline reliability
- Translate complex findings into concise narratives, presentations, and recommendations for technical and non-technical stakeholders
- Support AI data initiatives by helping build and evaluate models, measure features, and assess customer and business impact
Requirements:
- Bachelor's degree in a quantitative field such as Statistics, Economics, Mathematics, Computer Science, Engineering, or a related discipline; advanced degree preferred
- 5+ years of experience in data science, product analytics, decision science, or a closely related analytics role supporting product teams
- Strong SQL skills
- Proficiency in Python for data analysis, statistical modeling, predictive modeling, and data exploration
- Experience with PyTorch, scikit-learn, and other machine learning frameworks
- Familiarity with feature engineering, model selection, cross-validation, hyperparameter tuning, and performance evaluation
- Experience developing dashboards and visualizations for executive reporting and product decisions
- Strong understanding of product metrics, experimentation, hypothesis testing, and statistical analysis
- Experience working with large, messy, and multi-source datasets
- Excellent communication skills and ability to explain technical findings in plain language and influence stakeholders through data
- Experience supporting AI or ML-related product initiatives, model evaluations, or measurement frameworks preferred
- Experience in media, ad tech, mar tech, digital subscriptions, marketplaces, or other product-led businesses preferred
- Experience in cloud data environments and product instrumentation best practices preferred
- Experience in highly cross-functional environments with shifting priorities preferred
Benefits:
- Annualized base salary of $115,000–$120,000
- Variable compensation may be applicable
- Remote work arrangement
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