Senior Manage of Data Science

We’re looking for a Senior Manager of Data Science to build and execute data-driven systems that directly shape how Chemical Guys markets, forecasts, and grows. This role blends data engineering, modeling, and inference, with a strong emphasis on hands‑on development and implementation. You’ll be deeply involved in developing and improving Market Mix Models, Amazon Paid Search Optimization algorithms, and Forecasting frameworks — all built primarily in R and SQL.

This is an opportunity to take ownership of technically challenging, high‑impact analytics work while collaborating closely with business leaders.

• Develop and refine statistical and machine learning models that drive marketing optimization, forecasting, and pricing decisions.
• Build and maintain data pipelines and modeling infrastructure to ensure consistent, automated performance.
• Work closely with Marketing, Finance, and Operations teams to translate model output into actionable insights.
• Conduct deep‑drive analyses to support experimentation, performance measurement, and strategy evaluation.
• Continuously evaluate and improve data quality, feature engineering, and model interpretability.
• Collaborate with IT to ensure alignment on data infrastructure, governance, and model deployment standards.

Hybrid (Los Angeles, CA) 3 days onsite

Advanced Analytics

VP of Advanced Analytics

$140 - 160k annually plus bonus.

• Master’s degree (or higher) in Statistics, Data Science, Applied Mathematics, or related quantitative discipline.
• 5–8 years of experience in applied analytics or data science roles.
• Expertise in R and SQL, including model development, data manipulation, and workflow automation.
• Hands‑on experience with modeling techniques such as regression, Bayesian inference, time‑series forecasting, and optimization.
• Experience with marketing analytics or Market Mix Modeling (MMM) strongly preferred.
• Strong communication skills — able to explain analytical findings clearly to both technical and non‑technical audiences.
• Comfortable working in an agile, fast‑paced environment with minimal supervision.

• Experience with cloud‑based data systems (Big Query, Snowflake, Azure).
• Exposure to media data (Amazon Ads, Google Ads, Meta).
• Familiarity with dashboarding tools (Shiny, Power BI, Tableau).
• Understanding of data engineering concepts (ETL, workflow automation, modular pipeline design).