Senior Data Scientist

• Analyze marketplace dynamics across supply and demand, uncovering insights to improve conversion, fill rates, and operator performance.
• Design and evaluate experiments that test pricing strategies, inventory prioritization, and incentive programs for both consumers and storage operators.
• Build predictive models for customer acquisition, lead quality scoring, pricing elasticity, and churn forecasting.
• Partner with Product, Engineering, and Sales to develop tools and dashboards that guide marketplace health and operator decision-making.
• Support the rollout of new features (e.g., dynamic pricing, lead routing, inventory optimization) with data validation, success metrics, and performance analysis.
• Develop frameworks to balance occupancy and revenue across regions, seasons, and storage types.

What You Bring:

• 7+ years of experience in data science, ideally with exposure to marketplaces, real estate, local services, or platform ecosystems.
• Strong statistical background with expertise in experimentation, causal inference, and regression modeling.
• Proficiency in SQL and Python; experience working with large-scale data sets and modern data stacks (e.g., dbt, Airflow, Snowflake).
• Proven success influencing product strategy and commercial decisions using data.
• A practical, iterative approach to modeling balancing speed with rigor in a real-world environment.
• Experience collaborating cross-functionally with PMs, engineers, analysts, and business leaders.
• Comfort navigating noisy or incomplete data, especially in fragmented industries like self storage.

Bonus Points For:

• Experience building pricing, search, or lead quality models in a lead-gen or vertical marketplace business.
• Understanding of the self storage industry, including occupancy economics, customer behavior, and regional trends.

Familiarity with geospatial analysis, customer segmentation, or recommender systems.