Manager of Data Science; Marketing Job San Francisco area,California USA,IT/Tech

Position: Manager of Data Science (Marketing)

We’re looking for a Data Science Manager to architect and lead the next generation of marketing data science at Go Fund Me .
This role will build and scale the foundations of applied data science and AI that empower our Marketing, Growth, and Finance teams to make high-confidence, ROI-positive investment decisions.
You’ll serve as a player-coach for a talented group of experienced data scientists, driving innovation while ensuring excellence in delivery
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

Benefits

$600 annual fitness and wellness reimbursement
Wide range of health insurance options, including medical, dental, and vision (Go Fund Me covers 100% of employee premiums, and 80% of spouse and dependents)
Weekly massages
Standing desks
Fully-stocked kitchens & daily lunches
Team off-sites & monthly social events
Many of our offices are dog friendly
Enhanced parental leaves
10 paid holidays, 17 days of accrued vacation per year, unlimited sick time & three volunteer days
Caltrain GoPasses for our Bay Area commuters
$50/month for employees commuting to and from work (public transit and/or parking)
Quarterly volunteer events in each office to give back to our local communities
“Gives Back” program, where employees nominate fundraisers weekly for donations from Go Fund Me
401(k) retirement plan with company matching
Access to learning tools and resources, including a subscription to Udemy, guest speakers, and internal brown bag sessions

Master’s or Ph.D. in a quantitative field (Statistics, Mathematics, Economics, Computer Science, Physics, Operations Research or related), or equivalent applied experience
8+ years of experience in data science roles with direct impact on marketing, growth, or revenue optimization
Hands-on with data platforms (Snowflake, Databricks) and BI tools (Looker, Tableau, or equivalent)
Advanced proficiency in Python (Num Py, pandas, scikit-learn) and SQL (window functions, optimization)
Proven success in forecasting, optimization, and budget allocation models for marketing and growth functions
Deep experience with experimentation frameworks: A/B testing, causal inference, uplift modeling, and attribution models
Strong data storytelling and executive presentation abilities
Experience developing senior data scientists and elevating team practices
Exceptional communication skills with the ability to influence executive stakeholders and translate data into actionable business recommendations
Demonstrated ability to define a strategic vision for applied data science in marketing, balancing rapid experimentation with long-term infrastructure investments
Experience integrating with marketing APIs (Google, Meta, programmatic platforms) for campaign optimization
Familiarity with experimentation and web/mobile analytics platforms (Optimizely, Growth Book, Google Analytics, Amplitude)
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

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