What You'll Do

Solve real business problems with data: Own end-to-end data science work, from problem framing and data exploration to modeling, validation, and production impact.
Lead high-impact initiatives: Drive complex efforts such as vendor leakage detection and prevention, delivering measurable revenue or cost improvements.
Innovate on methods and approaches: Go beyond standard analyses by developing new metrics, models, or workflows when existing approaches fall short.
Build and productionize models: Design, build, and support production ML or LLM-powered solutions in collaboration with engineering and product partners.
Work deeply with data: Use SQL fluently to explore large datasets, build reliable data assets, and validate results.
Influence cross-functionally: Partner with Product, Engineering, Finance, and Operations to align on goals, tradeoffs, and execution plans.
Set technical direction (especially at L7): Raise the bar for data science quality, scalability, and impact across the organization through mentorship, design reviews, and technical leadership.

What You'll Bring

Proven track record of hands-on data science impact on real-world problems, not just research or dashboards.
Strong proficiency in SQL, with experience working directly on complex, large-scale datasets.
Experience building, shipping, or supporting production ML systems, preferably some exposure to LLM-based products or workflows.
Ability to independently scope ambiguous problems, identify the right data and methods, and drive work to completion.
Strong communication skills, with the ability to explain complex analyses and models to non-technical stakeholders.