Data Scientist, Product Analytics - 1040

Role Overview

About the team:

We are looking for a Data Scientist to support the product and operations teams responsible for ensuring buyer delivery promises are met, delivery issues minimized, and optimally resolved. As a Data Scientist working in this area you will work to deliver clear insights, and provide access to metrics, data, and tools needed for decision-making and optimization at all levels of the organization.The current team size is 3 FTEs.

About the Role:

In this role, you'll be a key partner, providing data-driven insights to improve the customer post order delivery experience and improve buyer LTV. You will work collaboratively with both internal analytics stakeholders, and fulfillment and customer experience ops and product teams.

Requirements

• Business analysis and advanced analytics: Partner with operations leaders and product managers within our Fulfillment and Customer Support operations & product teams to shed light on opportunities to mitigate order issues, improve issue resolution effectiveness, and drive buyer purchase frequency, through the advanced analytical techniques.
• Provide Ad-Hoc Analysis and Reporting: Utilize Google BigQuery to efficiently query, analyze, and interpret large datasets to answer prioritized ad-hoc business questions and support strategic decision-making.
• Collaborate and Communicate: Work closely with cross-functional teams, including Operations, Fulfillment and Customer Experience Specialists, to understand their needs and translate data insights into actionable strategies.
• Ensure Data Accuracy and Accessibility: Develop, maintain, and improve data rollups to guarantee data quality and provide reliable data sources for reporting and analysis.
• Develop Insightful Visualizations: Design and build interactive dashboards and reports in Looker to track key performance indicators (KPIs), identify trends, and communicate actionable insights to stakeholders.

Must-Haves

1. Experience with causal inference and analytical ML modelling (regression, clustering, random forest, propensity score matching etc.)
2. Experience with Looker and other data visualization tools.
3. Experience developing data rollups in SQL preferably on cloud data warehouses such as BigQuery

Nice-to-Haves

1. Experience working with order incident, customer resolution and fulfillment data (issue report rate, on time delivery, carrier performance etc.)
2. Experience working in a two sided marketplace environment
3. Familiarity with buyer LTV modelling in a non subscription environment
4. Familiarity with clickstream data (visits, events etc.)
5. Comfortable leveraging AI tools (Claude, Cursor etc.)

Details/Notes

• Provide general project support
• All work modes (remote/flex/on-site)
• May extend, depending on the needs of the team, budget availability, and contractor performance
• Interview process: 30-min manager screen, followed by a 30-60 min technical assessment (e.g. live coding session, technical deep dive, case study) with 1-2 members of the hiring team