Lead Machine Learning Scientist

Dave

5d • $174,000 - $224,000 • Remote

About The Position

Dave is looking for a Lead Machine Learning Scientist to own and scale ML-driven Marketing/Growth/Product capabilities. This role will drive how we use data and machine learning to improve acquisition, engagement, retention, and monetization across a multi-product ecosystem. You will help identify high-impact opportunities, building production-grade models, and shaping the roadmap for ML in Marketing/Growth. This is a highly strategic and hands-on role requiring both technical depth and business acumen.

Requirements

• 7+ years of experience in machine learning, data science, or a related field
• Proven experience building and scaling ML models in production environments
• Strong experience with marketing-related models (propensity, churn, LTV, targeting, etc.)
• Demonstrated ability to lead large, ambiguous, cross-functional projects
• Strong programming skills (Python, SQL) and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Familiarity with Marketing KPIs (CAC, ROAS etc)
• Strong communication skills—you can translate between technical and business audiences

Nice To Haves

• Experience in fintech or multi-product ecosystems
• Familiarity with attribution, MMM, or marketing measurement
• Experience with large-scale data platforms (e.g., Snowflake)

Responsibilities

• Architect and lead machine learning solutions across teams, driving multi-person, cross-functional initiatives
• Define and execute the roadmap for applying ML to improve marketing efficiency and growth
• Proactively identify high-impact opportunities where ML can drive step-function improvements
• Partner closely with Marketing, Product, and Finance to align ML investments with business priorities
• Lead development and deployment of core models, including propensity, churn prevention and intervention, Customer Lifetime Value (LTV), and cross-sell / next-best-action models
• Improve onboarding, targeting, personalization, and segmentation at scale
• Work across modeling lifecycle from problem formulation, training, calibration, and iteration in production
• Build agentic engineering workflows that accelerate development, testing, and documentation
• Analyze large and complex datasets; Identify and evaluate high-leverage internal and external data sources to improve model performance
• Build business cases for new data acquisition and lead onboarding efforts
• Ensure models are scalable, measurable, and tightly integrated into marketing workflows
• Continuously evaluate and improve marketing spend efficiency through ML-driven insights and models
• Identify and resolve cost inefficiencies across models and pipelines
• Design and optimize reward and incentive strategies (e.g., referral incentives, promotional offers) to maximize user acquisition, activation, and retention while managing cost efficiency
• Develop models to determine optimal reward levels and targeting, balancing conversion lift with incremental cost to improve ROI
• Evaluate and measure incrementality of rewards and promotions using experimentation (A/B testing, uplift modeling) to ensure incentives drive true behavioral change rather than subsidizing existing demand
• Set standards for model development, experimentation, and validation
• Promote adoption of modern ML techniques, leverage pre-trained models, including effective use of AI/LLMs where applicable

Benefits

• Flexible hours and virtual-first work culture with a home office stipend
• Premium Medical, Dental, and Vision Insurance plans
• Generous paid parental and caregiver leave
• 401(k) savings plan with matching contributions
• Financial advisor and financial wellness support
• Flexible PTO and generous company holidays, including Juneteenth and Winter Break
• All-company in-person events once or twice a year and virtual events throughout to connect with your team members and leadership team

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed