Data Scientist, Support
About the Team The User Operations team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products.
What this role actually needs.
About the Team The User Operations team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. Responsibilities: - Explore large support and product datasets to uncover trends, volume drivers, and user‑experience pain points, distilling findings into clear, actionable narratives. - Build, enhance, and maintain self‑serve dashboards and reporting tools, enabling non‑technical teams to answer their own data questions. - Establish a unified metrics taxonomy for service‑health and performance—and build automated data‑sharing pipelines and scorecards with our BPO partners to ensure everyone operates from the same real‑time view of success - Leverage LLMs to build bespoke classifiers that automatically label and segment inbound volumes—powering smarter routing, richer self‑serve insights, and swifter root‑cause analysis. - Partner with Data Engineering to ensure reliable pipelines, implement data‑quality checks, and document sources of truth. - Jump into high‑priority special projects to conduct bespoke deep‑dive analyses and deliver clear, strategic recommendations to leadership. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Data Scientist, Support role.
- Explore large support and product datasets to uncover trends, volume drivers, and user‑experience pain points, distilling findings into clear, actionable narratives.
- Build, enhance, and maintain self‑serve dashboards and reporting tools, enabling non‑technical teams to answer their own data questions.
- Establish a unified metrics taxonomy for service‑health and performance—and build automated data‑sharing pipelines and scorecards with our BPO partners to ensure everyone operates from the same real‑time view of success
- Leverage LLMs to build bespoke classifiers that automatically label and segment inbound volumes—powering smarter routing, richer self‑serve insights, and swifter root‑cause analysis.
- Partner with Data Engineering to ensure reliable pipelines, implement data‑quality checks, and document sources of truth.
- Jump into high‑priority special projects to conduct bespoke deep‑dive analyses and deliver clear, strategic recommendations to leadership.
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United States tech market
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Compensation read
$230K - $255K is visible before the click, so candidates can compare the role against local market expectations before applying.
Work authorization read
Current extracted signal: United States residents. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
Hybrid roles in San Francisco should be compared against commute, local salary bands, and nearby employer demand.
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Source: jobs.ashbyhq.com · Source ID: 1f37ae5b-791a-4505-9575-183cc4bb9d5e · Confidence: 97/100 · Last checked: May 7, 2026
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