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Senior/Staff Data Scientist, Infrastructure

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Glean

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Location:
United States , San Francisco Bay Area

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

175000.00 - 250000.00 USD / Year
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Job Description:

Glean is building a world-class data organization spanning data science, applied science, data engineering, and business analytics. This role sits within the Growth and Enterprise Readiness data science team, with a primary focus on pricing, billing, and enterprise usage, alongside broader time-to-value and deployment health metrics. In this role, you’ll work at the intersection of Product, Finance, Infrastructure, and Post-Sales to ensure Glean’s pricing and enterprise experience are grounded in clear, trusted data.

Job Responsibility:

  • Become a deep expert in Glean’s product telemetry, billing data, and platform systems, partnering closely with Product, Finance, and Infrastructure to self-serve insights
  • Develop and evolve metrics that capture enterprise readiness, deployment health, and time-to-value, from initial rollout to sustained adoption
  • Drive deployment and infrastructure cost optimization by analyzing usage patterns, workload drivers, and scaling behavior across customers
  • Partner with platform and infrastructure teams to model and optimize the economics of core systems such as connectors, indexing, and knowledge graph infrastructure, ensuring margins scale sustainably with usage growth
  • Support pricing, packaging, and monetization decisions through thoughtful analysis of usage, consumption, and cost drivers
  • Improve observability and data quality for billing and enterprise-critical workflows, identifying gaps and driving alignment across systems
  • Build analytics and models to support security and trust initiatives, including threat detection, abuse patterns, and monitoring for enterprise-critical products
  • Analyze and improve the cost efficiency of compute-intensive workflows (eg: mining and indexing), identifying trade-offs between product value, performance, and unit economics
  • Lead cross-functional data science projects end-to-end, translating ambiguous problems into clear, actionable insights

Requirements:

  • 7+ years of experience in a highly quantitative data science role
  • Degree in Statistics, Mathematics, Computer Science, or a related field
  • Strong proficiency in SQL and Python
  • Experience working with modern data stacks (e.g., dbt, analytics engineering pipelines)
  • Experience analyzing nascent, complex datasets and translating them into clear, actionable insights
  • A strong product and business mindset, with experience defining KPIs, guardrail metrics, and dashboards that influence decisions
  • Solid grounding in statistics, including experimentation and non-experimental methods
  • Ability to independently own projects end-to-end, from problem framing to delivery
  • Clear, concise communication skills, with the ability to explain complex analyses to both technical and non-technical audience

Nice to have:

  • Experience in B2B SaaS, especially in the enterprise AI space
  • A very strong sense of ownership and self-motivation
  • Good at managing evolving priorities while successfully delivering core initiatives
  • Experience working with collaborators across large time zone differences
What we offer:
  • Medical, Vision, and Dental coverage
  • Generous time-off policy
  • Opportunity to contribute to your 401k plan
  • Home office improvement stipend
  • Annual education and wellness stipends
  • Vibrant company culture through regular events
  • Healthy lunches daily

Additional Information:

Job Posted:
February 18, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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