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Metropolis

Checkout-free parking payments via computer vision

Senior Data Scientist - Growth Marketing

Data ScienceConfirmed live in the last 24 hours
Full-timeChicago, IL, USA

About the Job

Requirements

  • A 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 lifetime value/customer acquisition cost dynamics.
  • Hands-on experience with statistical experimentation and causal inference techniques, including A/B testing, geo-testing, synthetic controls, and media mix modeling.
  • Experience partnering with senior executives in Growth, Product, and Finance to drive measurable business growth.
  • Analytical, problem-solving, and communication skills to make complex data insights intuitive and actionable.
  • Experience using AI tools to transform analytical workflows into responsive, high-output processes.

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 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 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.
  • Use AI tools and modern analytics frameworks to transform static analytical workflows into responsive, high-output processes.

Desired Qualifications

  • Experience with cloud platforms, including AWS S3, SageMaker, and Airflow.
  • Experience with cloud data warehouses and modern data tools, including 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 to produce high-quality data science procedures.

About the Company

Metropolis

Checkout-free parking payments via computer vision

Metropolis is a technology-driven facility-management company that focuses on parking solutions using computer vision to enable checkout-free payments. Its system detects vehicles and parking events via cameras and sensors, allowing drivers to pay automatically without stopping at a gate. The platform integrates into real estate operations, Class A office buildings, multi-garage complexes, and valet services to improve asset productivity and streamline operations. Compared with others, Metropolis supports a wide customer base across North America, operates in over 360 cities, processes more than $4 billion in payments annually, and has grown through significant funding rounds and the acquisition of SP Plus Corporation. Its goal is to expand its platform’s capabilities and market reach, helping property owners and managers increase efficiency and revenue by embedding its payment and facility-management tools directly into daily operations.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$3.5B
Headquarters
Santa Monica, CA
Founded
2017

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