Senior Data Scientist

• Develop, deploy and maintain predictive models for lifetime value (LTV), churn and retention across mobile apps and web/browser products
• Own the modeling roadmap from problem framing through production and ongoing monitoring
• Build cohort and LTV models informing user acquisition budgets and payback decisions
• Build user segmentation and propensity models supporting personalization and targeting
• Improve model accuracy through validation, backtesting and new data sources
• Design experiments and causal analyses measuring the impact of product and marketing changes
• Identify behavioral signals predicting conversion, churn and long-term value
• Apply LLMs and machine learning to classify unstructured text and behavioral signals into interest categories and product and brand intent
• Partner with data engineering to productionize models and keep inputs reliable
• Build internal AI-powered analytics tools and data products
• Explain model results, assumptions and confidence levels to stakeholders and leadership
• Set modeling standards, documentation and team best practices
• Mentor analysts and data scientists and share best practices across the team

• 5+ years of experience in data science, statistical modeling or machine learning, ideally with consumer app or web data
• Strong Python (pandas, scikit-learn or similar) and advanced SQL
• Experience deploying models to production and monitoring them over time
• Solid grounding in statistics, forecasting and experimentation
• Hands-on experience with LLM APIs, prompt design or building AI-powered data tools
• Daily use of AI tools as a development partner, such as Claude, Claude Code or Claude Cowork
• Sound judgment with incomplete or noisy data; structure the problem before reaching for a tool
• Strong communication skills, including turning complex analysis into clear business recommendations
• Fluent English and at least 4 hours of overlap with US Eastern business hours
• Experience with ad-monetized or subscription consumer apps
• Experience with recommendation systems, personalization or audience segmentation for ad targeting
• Experience with ML platforms on AWS or Google Cloud, such as SageMaker or Vertex AI
• Familiarity with MLOps and orchestration tools such as MLflow, Airflow or dbt
• Familiarity with Bayesian methods, uplift modeling or multi-armed bandits

• Full-time contract through a payroll platform
• Remote work allocated at the client
• Opportunity to work with first-class companies around the globe