Manager, Data Science (Marketing)

Job Build a strong AI and data science foundation: Develop scalable pipelines, reusable modeling frameworks, and robust experimentation platforms to support marketing and growth decision-making.

Lead end-to-end data science & AI projects: From requirements gathering through feature engineering, modeling, validation, deployment, and monitoring.

Establish best practices: Champion standards in model governance, reproducibility, data quality, and system reliability to ensure sustainable and trustworthy AI adoption.

Drive marketing science innovation: Apply advanced methods—causal inference, uplift modeling, multi-touch attribution, and media mix modeling—to unlock insights and optimize spend.

Advance forecasting & ROI modeling: Deliver budget allocation frameworks and predictive models that guide long-term roadmap planning and marketing efficiency.

Partner cross-functionally: Work closely with Marketing, Growth, Product, Engineering, and Finance leaders to align analytics initiatives with revenue impact.

Invest in people: Mentor, coach, and elevate a team of high-performing data scientists; foster a culture of technical rigor, curiosity, and applied innovation.

Push the frontier of applied AI in marketing: Evaluate emerging generative and predictive AI approaches for audience segmentation, creative optimization, personalization, and campaign efficiency.

Experience & Education

• 8+ years of experience in data science roles with direct impact on marketing, growth, or revenue optimization.
• Master’s or Ph.D. in a quantitative field (Statistics, Mathematics, Economics, Computer Science, Physics, Operations Research or related), or equivalent applied experience.

Technical Skills

• Advanced proficiency in Python (NumPy, pandas, scikit-learn) and SQL (window functions, optimization).
• Deep experience with experimentation frameworks: A/B testing, causal inference, uplift modeling, and attribution models.
• Proven success in forecasting, optimization, and budget allocation models for marketing and growth functions.
• Hands-on with data platforms (Snowflake, Databricks) and BI tools (Looker, Tableau, or equivalent).
• Strong data storytelling and executive presentation abilities.

Leadership & Collaboration

• Exceptional communication skills with the ability to influence executive stakeholders and translate data into actionable business recommendations.
• Experience developing senior data scientists and elevating team practices.
• Demonstrated ability to define a strategic vision for applied data science in marketing, balancing rapid experimentation with long-term infrastructure investments.

Preferred

• Familiarity with experimentation and web/mobile analytics platforms (Optimizely, GrowthBook, Google Analytics, Amplitude).
• Experience integrating with marketing APIs (Google, Meta, programmatic platforms) for campaign optimization.
• Prior exposure to generative AI or LLMs in marketing use cases (e.g., personalization, targeting, creative analysis).
• Knowledge of multi-arm and contextual bandit algorithms for adaptive experimentation and continuous marketing optimization.
• Familiarity with ML ops practices: version control, model monitoring, scalable ETL frameworks.