About The Position

As a Senior Data Scientist at StreetEasy, you will help shape marketing strategy through experimentation, measurement, and data-driven insight. Embedded within the marketing team, you will work across initiatives such as A/B testing, lifecycle optimization, and marketing mix measurement to improve customer experience and drive high-quality traffic to StreetEasy’s websites and apps. This is a high-impact role for someone who enjoys connecting advanced analytics to clear business decisions and cross-functional action.

Requirements

  • Bachelor’s degree in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field, or equivalent practical experience.
  • 5+ years of experience using data to solve complex business problems in a professional environment.
  • Strong proficiency in SQL and Python, or comparable programming experience, with experience using tools such as Tableau and Databricks.
  • Experience designing, running, and interpreting experiments, with a strong foundation in statistical analysis and testing methodologies.
  • Strong business acumen and product sense, with the ability to connect business goals to practical, data-driven recommendations.
  • Excellent communication skills and experience working cross-functionally with partners across engineering, product, and marketing.
  • Ability to solve problems efficiently, prioritize high-impact work, and adapt in a fast-moving environment.

Nice To Haves

  • Broad data science experience spanning exploratory analysis through advanced modeling; experience with machine learning, dbt, marketing attribution, MMM, or AI tools is a plus.
  • Value the experience and perspective of candidates with non-traditional backgrounds. Encourage to apply if you have transferable skills or related experiences.

Responsibilities

  • Lead end-to-end experimentation for the marketing team, including A/B test design, analysis, and interpretation of results.
  • Drive measurement approaches that improve marketing effectiveness, including marketing mix modeling and related performance analyses.
  • Translate customer insights, metrics, and analytical findings into clear recommendations for technical and non-technical partners.
  • Identify complex business problems, frame them clearly, and partner across teams to deliver scalable, data-informed solutions.
  • Build reusable analytical frameworks, including simulations and causal inference approaches, to support broader team decision-making.
  • Create dashboards and reporting in tools such as Tableau and Databricks to improve visibility into performance and opportunities.
  • Partner with engineering to improve data quality, strengthen data collection, and build transformation pipelines using tools such as dbt.
  • Mentor junior team members and champion data-informed decision-making across the organization.

Benefits

  • equity awards based on factors such as experience, performance and location
  • Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.
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