Senior Data Scientist (Growth Marketing)

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 and enjoy a range of benefits, including health insurance, equity options, wellness benefits, a 401(k) match, parental leave, unlimited PTO, paid holidays, and more.

• 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
• Experience leveraging AI tools to transform static workflows into responsive, high-output processes
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field
• Hands-on experience with statistical experimentation and causal inference techniques such as A/B testing, geo-testing, synthetic controls, and media mix modeling
• Advanced proficiency in Python and SQL for complex data manipulation, statistical modeling, and predictive analytics
• Excellent analytical, problem-solving, and communication skills to make complex data stories intuitive and actionable
• 6+ years of proven experience as a Data Scientist or Analytics Lead, with a distinct focus on growth marketing, performance media, or adtech
• Deep domain expertise in growth measurement frameworks, multi-touch attribution, cohort retention modeling, and LTV/CAC dynamics
• 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