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Salary: USD 190,000 - 220,000 / annual
Metropolis is building AI systems to make the real world responsive, pioneering what they call the Recognition Economy. The company transforms everyday experiences—starting with parking—into seamless, intelligent interactions. They are expanding their AI layer across retail and hospitality.
You will serve as the primary quantitative partner to Growth Marketing leadership, translating massive real-world transactional and behavioral datasets into engines for user acquisition, retention, and gross profit expansion.
Key responsibilities:
- Design, deploy, and refine predictive models for Multi-Touch Attribution (MTA), Customer Lifetime Value (CLV), and Customer Acquisition Cost (CAC) efficiency to guide multi-channel marketing budget allocation
- Conduct deep-dive cohort analyses and retention modeling to uncover drivers of user conversion, repeat behavior, and churn across the location-based growth funnel
- Lead the growth experimentation roadmap by designing, executing, and analyzing A/B tests, geo-experiments, holdout tests, and incrementality studies across digital and physical acquisition channels
- Partner directly with Growth Marketing and Finance leaders to optimize unit economics, justify marketing spend against gross profit targets, and set channel-level growth goals
- Collaborate with analytics and data engineering teams to establish event tracking requirements, build scalable growth data pipelines, and develop automated executive dashboards
- Utilize advanced AI tools and modern analytics frameworks to transform static analytical workflows into responsive, high-output processes
The role requires 4 days per week in-office to foster collaboration and culture.
REQUIREMENTS:
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field
- 6+ years of proven experience as a Data Scientist or Analytics Lead, with distinct focus on growth marketing, performance media, or adtech
- 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 (A/B testing, geo-testing, synthetic controls, media mix modeling)
- Strong business acumen with track record of partnering with senior executives in Growth, Product, and Finance to drive measurable bottom-line growth
- 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
PLUS (not required):
- Experience with cloud platforms (AWS S3, SageMaker, Airflow)
- Cloud data warehouses and modern data tools (Snowflake, dbt, Looker, Tableau)
- Media Mix Modeling frameworks (Robyn, LightweightMMM)
- Machine learning frameworks (scikit-learn, TensorFlow, PyTorch) applied to user segmentation or churn prediction
- Ability to write clean, efficient, robust, well-commented code
