Underdog needs to measure, optimize, and forecast user acquisition performance as marketing investment grows, requiring robust marketing measurement models and an analytics framework.
Requirements
- Hands-on experience building and maintaining Marketing Mix Models (MMM) or equivalent budget optimization frameworks.
- Familiarity with Bayesian modeling, hierarchical models, or probabilistic programming.
- Proficiency in Python for modeling and SQL for data manipulation.
- Strong understanding of experimentation design, incrementality, and causal inference.
- Familiarity with cloud-based tools and data workflows (e.g., AWS, GCP, dbt, Airflow).
- Experience with LTV, attribution, or uplift models in a UA or growth setting.
- Experience with marketing platforms or MMP tools (e.g., Google Ads, Meta Ads Manager, AppsFlyer).
Responsibilities
- Own the Marketing Mix Modeling (MMM) process including design, calibration, and iteration.
- Translate MMM insights into channel-level budget recommendations and marketing strategy guidance.
- Design and analyze experiments to understand the incremental impact of marketing campaigns.
- Build and iterate on models for user acquisition (UA), attribution, and LTV.
- Develop scenario testing tools for marketing planning and spend simulation.
- Automate recurring campaign reporting and performance diagnostics.
- Partner with Growth, Finance, and Data Engineering to align spend optimization and forecasting models with business goals.
Other
- A degree in Statistics, Economics, Math, Computer Science, or related technical field.
- 5+ years of experience in data science or analytics, with a strong focus on marketing or growth.
- Proven ability to influence cross-functional partners with compelling, data-backed recommendations.
- Prior work in consumer tech, sports betting, fantasy sports, or mobile gaming.
- This position may require sports betting licensure based on certain state regulations.
