Senior Data Scientist, Growth Marketing

Metropolis•Seattle, WA

1d•$190,000 - $220,000•Onsite

About The Position

Metropolis is seeking a Senior Data Scientist, Growth Marketing, to serve as the primary quantitative partner to Growth Marketing leadership. The role turns large transactional and behavioral datasets into strategies and models that support user acquisition, retention, and gross profit growth. It requires expertise in marketing measurement and causal inference, including multi-touch attribution, customer lifetime value modeling, and rigorous experimentation. The successful candidate will translate analytical findings into clear business strategies for stakeholders across Growth, Product, and Finance. The position partners with marketing and finance leaders to optimize unit economics and guide channel-level growth goals. It also collaborates with analytics and data engineering teams on event tracking, scalable data pipelines, and executive dashboards, while using AI tools and modern analytics frameworks to improve analytical workflows. Metropolis follows an office-first model requiring corporate team members to work on-site at least four days per week.

Requirements

Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field.
At least 6 years of experience as a Data Scientist or Analytics Lead, focused on growth marketing, performance media, or adtech.
Advanced proficiency in Python and SQL for complex data manipulation, statistical modeling, and predictive analytics.
Deep expertise in growth measurement frameworks, multi-touch attribution, cohort retention modeling, and LTV/CAC dynamics.
Hands-on experience with statistical experimentation and causal inference methods, such as A/B testing, geo-testing, synthetic controls, and media mix modeling.
Strong business acumen and experience partnering with senior executives in Growth, Product, and Finance to drive measurable business growth.
Excellent analytical, problem-solving, and communication skills, including the ability to make complex data insights clear and actionable.
Experience using AI tools to transform static workflows into responsive, high-output processes.

Nice To Haves

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 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 for high-quality data science procedures.

Responsibilities

Design, deploy, and refine predictive models for multi-touch attribution, customer lifetime value, and customer acquisition cost efficiency to guide multi-channel marketing budget allocation.
Conduct cohort analyses and retention modeling to identify drivers of conversion, repeat behavior, and churn across the location-based growth funnel.
Lead growth experimentation by designing, executing, and analyzing A/B tests, geo-experiments, holdout tests, and incrementality studies across digital and physical acquisition channels.
Partner with Growth Marketing and Finance leaders to optimize unit economics, evaluate marketing spend against gross profit targets, and set channel-level growth goals.
Collaborate with analytics and data engineering teams to define event tracking requirements, build scalable growth data pipelines, and develop automated executive dashboards.
Use advanced AI tools and modern analytics frameworks to make analytical workflows more responsive and productive.