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Salary: USD 170,000 - 200,000 / annual
Metropolis Technologies 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 using computer vision and AI.
As Senior Data Scientist, Growth Marketing, you will be the primary quantitative partner to Growth Marketing leadership, responsible for turning large-scale transactional and behavioral datasets into engines for user acquisition, retention, and 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
Metropolis values in-person collaboration and operates an office-first model requiring employees to be on-site at least four days per week.
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 such as A/B testing, geo-testing, synthetic controls, and 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 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
