Applied Science, Growth

What you'll do

• Build models and decision systems to support profitable growth through customer acquisition and engagement.
• Develop intent, conversion, and customer lifetime value models to optimize engagement.
• Build marketing measurement and optimization systems to guide budget allocation across channels and markets.
• Apply causal inference to experimental and observational data to estimate incremental marketing impact.
• Translate model findings into clear recommendations for technical and business partners.
• Move quickly from research and prototyping to production while owning ongoing model evaluation.
• Build maintainable software and production ML systems using Python.

What we're looking for

• Strong Python skills with experience building maintainable software and contributing to production ML systems.
• Experience taking predictive models from problem definition through training, deployment, evaluation, and iteration.
• Strong foundation in classification and statistical modeling.
• Applied experience in causal inference and experimental design, including estimating incremental effects and reasoning about confounding.
• Ability to evaluate models using both predictive performance and business outcomes.
• Comfort working with imperfect data and translating findings into clear recommendations for technical and business partners.
• Advanced degree (MS or PhD preferred) in statistics, economics, computer science, mathematics, operations research, or a related quantitative field.
• Experience in media targeting, marketing mix modeling, multi-touch attribution, or budget allocation (preferred).