Senior Data Scientist (Growth Marketing)
Metropolis
Los Angeles, United States Posted October 26, 2026
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Salary Range
$190,000 - $220,000
Job Description
Join our team as a Senior Data Scientist focused on Growth Marketing. In this role, you will design and refine predictive models, conduct deep-dive analyses, lead growth experimentation, and collaborate with various teams to optimize marketing strategies. You will have the opportunity to work in a hybrid environment, receive competitive benefits, and contribute to the company's growth and success.
- Design, deploy, and refine predictive models for Multi-Touch Attribution (MTA), Customer Lifetime Value (CLV), and Customer Acquisition Cost (CAC) efficiency.
- Conduct deep-dive cohort analyses and retention modeling to uncover drivers of user conversion, repeat behavior, and churn.
- Lead the growth experimentation roadmap by designing, executing, and analyzing A/B tests, geo-experiments, holdout tests, and incrementality studies.
- Strong business acumen with a track record of partnering with senior executives in Growth, Product, and Finance to drive measurable bottom-line growth
- Advanced proficiency in Python and SQL for complex data manipulation, statistical modeling, and predictive analytics
- Deep domain expertise in growth measurement frameworks, multi-touch attribution, cohort retention modeling, and LTV/CAC dynamics
- Hands-on experience with statistical experimentation and causal inference techniques such as A/B testing, geo-testing, synthetic controls, and media mix modeling
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field
- 6+ years of proven experience as a Data Scientist or Analytics Lead, with a distinct focus on growth marketing, performance media, or adtech
- Excellent analytical, problem-solving, and communication skills to make complex data stories intuitive and actionable
- Experience leveraging AI tools to transform static workflows into responsive, high-output processes
- Experience with cloud platforms, including AWS S3, SageMaker, and Airflow
- Experience with cloud data warehouses and modern data tools such as Snowflake, dbt, Looker, and Tableau
- Familiarity with Media Mix Modeling (MMM) frameworks including Robyn and LightweightMMM
- Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch applied to user segmentation or churn prediction
- Ability to write clean, efficient, robust, and well-commented code to produce high-quality data science procedures
Required Skills
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