Responsibilities
- Identify, prioritize, and execute opportunities to scale marketing efforts across acquisition, engagement, and retention.
- Evaluate the incremental impact of marketing investments through experimentation (A/B testing, causal inference) at both macro and granular levels (channel, tactic, creative, etc.).
- Build, operationalize, and iterate on data science solutions such as Marketing Mix Models, Audience Scoring, and Customer Segmentation to drive intelligent marketing strategies.
- Provide closed-loop data science support for audience-centric marketing, including audience sizing, experiment design, segmentation, and targeting model development.
- Support pricing, promotions, and other key business decisions through experimentation and ad hoc analysis.
Basic qualifications
- M.S. or B.S. in Math, Economics, Statistics, Engineering, Computer Science, or a related quantitative field
- 6+ years of industry experience as a Data Scientist (or equivalent)
- Advanced SQL expertise
- Expert-level experience with Python programming
- Deep knowledge of experimental design and causal inference
- Strong analytical and causal reasoning mindset
- Expertise in predictive modeling and statistical/machine learning techniques
- Experience applying predictive modeling to marketing use cases (e.g., CLTV, churn prevention, targeting)
- Fluency with Python ML libraries (e.g., Scikit-learn, PyTorch)
- Proficiency with data visualization and dashboard tools (e.g., Looker, Tableau)
Preferred qualifications
- Bias for action and a first-principles, systems-thinking approach
- Proven ability to independently initiate and complete end-to-end projects
- Prior experience in growth marketing (CRM and/or paid media)
- Solid understanding of the advertising and martech landscape and trends
- Experience in finance, fintech, or technology industries
- Background in marketing or product data science or consulting
- Hands-on experience with Databricks
- Experience applying econometric modeling (e.g., MMM) to optimize spend and maximize ROAS
- Knowledge of advanced data science techniques such as Bayesian statistics, Bandit models, and Net Lift modeling
Benefits
- Competitive salary and performance bonus
- 401(k) with employer match
- Exceptional health insurance with minimal out-of-pocket costs
- Fitness subsidy
- Free in-office lunches and snacks (if applicable)
- Autonomous, flexible work environment
- Customer-driven culture
- Opportunity to build products that make a real difference in people’s lives
Tags & focus areas
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