Lead Data Scientist, Philo

• 10+ years of professional experience in data science/analytics with demonstrated proficiency in Python, SQL, or R and statistical modeling
• 3+ years of experience leading marketing analytics or growth data science teams
• Deep expertise in marketing attribution methodologies (MMM, MTA, incrementality testing)
• Excitement to leverage the latest LLM tools to improve workflows and efficiency
• Strong experience with Bayesian methods for hierarchical modeling and ridge regression
• Proven track record of building and deploying marketing measurement systems at scale
• Experience with customer lifetime value modeling and cohort-based forecasting
• Deep experience in building robust data models for marketing analytics
• Experience mentoring data scientists on marketing analytics best practices
• Excellent communication skills with ability to translate complex attribution insights to marketing teams
• Strong business acumen with ability to connect marketing metrics to financial outcomes

Desirable

• Philo is looking for a Lead Data Scientist (Growth & Performance Marketing) to join our team and help elevate our marketing analytics and attribution practice
• This role will provide senior leadership in building sophisticated marketing measurement systems, establishing methodological rigor for growth analytics, and coaching our data science team to deliver high-impact solutions that optimize customer acquisition and lifetime value
• You have strong opinions about what world-class marketing attribution looks like and are passionate about driving efficient growth
• You will work across marketing, finance, and product teams and have a keen sense of how to connect marketing investments to business outcomes and customer value
• Set the roadmap and model best practices for marketing and growth sciences at Philo
• Lead the development of unified marketing measurement approaches combining Marketing Mix Modeling (MMM), Multi-touch Attribution (MTA), and incrementality testing
• Partner with marketing leadership and C-Suite to optimize marketing spend allocation and Return on Ad Spend (RoAS)
• Establish and evangelize methodological standards for marketing measurement and causal inference
• Build frameworks for Customer Lifetime Value (CLV) modeling and customer acquisition cost (CAC) optimization
• Coach and mentor data scientists on advanced attribution techniques and marketing analytics
• Develop and maintain marketing attribution models using tools like Robyn and custom solutions
• Lead geo-experimentation and matched market testing initiatives
• Build self-service dashboards and tools for marketing performance monitoring
• Collaborate with finance on budgeting and forecasting models
• Champion data-driven decision making in growth strategy and channel optimization
• Represent the data science team in marketing strategy and budget planning discussions