Senior Data Scientist, Growth Marketing

Description

The company builds AI that makes physical spaces respond to people, starting with parking and expanding into retail and hospitality.

The data team is growing. This role is the main quantitative partner to Growth Marketing leadership, working on user acquisition, retention and gross profit growth using large sets of real-world transaction and behavior data.

Responsibilities

• Build and maintain predictive models for multi-touch attribution, customer lifetime value and customer acquisition cost efficiency, which guide how the multi-channel marketing budget is split.
• Run in-depth cohort and retention analyses to find what drives conversion, repeat use and churn across the location-based growth funnel.
• Own the growth experiment plan by designing, running and interpreting A/B tests, geo experiments, holdout tests and incrementality studies across digital and in-person channels.
• Work directly with Growth Marketing and Finance leaders on unit economics, on justifying spend against gross profit targets and on setting channel growth goals.
• Work with analytics and data engineering teams to define event tracking, build scalable growth data pipelines and create automated executive dashboards.
• Apply AI tooling and modern analytics frameworks to replace static analysis routines with faster, higher-volume processes.

Requirements

• Combine strong modeling skills with the ability to turn findings into clear business strategy for senior stakeholders in Growth, Product and Finance.
• A bachelor's or master's degree in computer science, mathematics, statistics, economics or another quantitative field.
• 6+ years as a data scientist or analytics lead, with a clear focus on growth marketing, performance media or adtech.
• Advanced Python and SQL for data manipulation, statistical modeling and predictive analytics.
• Deep knowledge of growth measurement, multi-touch attribution, cohort retention modeling and LTV/CAC dynamics.
• Hands-on experience with experimentation and causal inference, such as A/B testing, geo testing, synthetic controls and media mix modeling.
• Solid business judgment and a record of working with senior executives in Growth, Product and Finance to deliver measurable bottom-line growth.
• Strong analytical, problem-solving and communication skills, so complex data is clear and actionable.
• Experience using AI tools to make routine workflows faster and higher in output.
• Plus: experience with AWS S3, SageMaker and Airflow.
• Plus: experience with cloud data warehouses and modern data tools such as Snowflake, dbt, Looker and Tableau.
• Plus: familiarity with Media Mix Modeling frameworks such as Robyn and LightweightMMM.
• Plus: hands-on machine learning with scikit-learn, TensorFlow or PyTorch for user segmentation or churn prediction.
• Plus: ability to write clean, efficient, robust and well-commented code for high-quality data science work.

Conditions

The corporate team works office-first and must be on-site at least 4 days a week.

The anticipated base salary is $190,000 USD to $220,000 USD per year.

Final base pay depends on qualifications, years of relevant experience, distinctive skills, education, certifications or licenses, and location of residence or workplace.

An automated decision tool may be used to assess applications against the listed qualifications, and related data is kept for as long as reasonably necessary, becoming part of employee records if you are hired.

Benefits

• Healthcare benefits, a 401(k) plan, short-term and long-term disability coverage and basic life insurance.
• A stock option plan, bonus plans and other extras as part of total compensation, with base pay as one component.