Job description

Who we are The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it. Who you are Metropolis is seeking a Senior Data Scientist, Growth Marketing to join our growing data team. In this role, you will serve as the primary quantitative partner to our Growth Marketing leadership, turning massive real-world transactional and behavioral datasets into engines for user acquisition, retention, and gross profit expansion. You bring a deep background in marketing measurement and causal inference, with proven experience building multi-touch attribution systems, modeling customer lifetime value (LTV), and designing rigorous marketing experiments. You excel not only at building complex predictive models, but also at translating high-level data insights into clear business strategies for cross-functional stakeholders across Growth, Product, and Finance. What you'll do 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 our 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 What we're looking for 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 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 a 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 While not required, these are a plus: 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 4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection. When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $190,000 USD to $220,000 USD annually. The actual base pay offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis’s total compensation package, which usually includes: healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-RR1 #LI-Onsite Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting. As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records. Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs — without regard to race, color, religion, sex (including gender identity, sexual orientation, and pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law. We are committed to providing a welcoming, accessible hiring experience. If you need a reasonable accommodation for any part of the application or interview process, please reach out to us at recruiting@metropolis.io .

Requirements

Must-haves

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 our 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
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
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 a 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
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

goaipythonsqlawsmachine learning

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

401(K)