Senior/Staff Applied Scientist

Details

Glean is building a world-class Data Organization composed of product data science, applied science, data engineering, and business intelligence groups. This applied science role is based in the San Francisco office.

Responsibilities

• Collaborate with product data science and engineering teams to identify techniques, tooling, and process improvements for online A/B experimentation and rigorous decision-making across relevant product domains.
• Develop and maintain the A/B experimentation platform based on stakeholder feedback.
• Write code or identify vendors to deploy experimentation techniques to production in a scalable manner that is easy for engineering, product data science, product management, and design teams to use.
• Conduct end-to-end evaluations of use cases such as document and URL uploads, including evaluation set generation, evaluation criteria, and methods for interpreting results.
• Break down end-to-end evaluations into granular evaluations of tasks and skills, including content summarization, analysis and generation, multi-step reasoning and strategizing, tool selection and use, coding, and system design.
• Design, develop, and own best practices, tools, and processes for evaluation problems such as query intent classification, applying statistical principles to handle LLM stochasticity, and industry benchmarking.

Requirements

• A master's degree holder with 5+ years of experience, or a PhD holder with 3+ years of experience. The degree should be in statistics, mathematics, computer science, or another quantitative field.
• Strong skills in statistics and/or machine learning, with experience applying them to tangible improvements in products, internal tools, and processes in a pragmatic, business-focused way.
• Very strong proficiency in Python, including the ability to maintain an internal source-controlled library used by dozens of people.
• Concise and precise written and verbal communication skills, with strong technical documentation abilities.
• Proficiency in SQL and the modern data stack, such as source-controlled dbt pipelines for ETL/ELT.
• Experience defining product KPIs and guardrail metrics, creating dashboards, and analyzing raw data to derive strategic insights.
• Experience in B2B SaaS.
• Experience with ranking, developing, and maintaining A/B experimentation platforms and/or machine learning measurement problems.
• Passion for using AI to improve the productivity of data teams and non-data professionals.

Work Arrangement

This is a hybrid role requiring four days per week in the San Francisco office.

Compensation And Benefits

The standard base salary range is $180,000–$330,000 annually. Compensation may vary based on location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

Benefits include medical, vision, and dental coverage; generous time off; a 401(k) plan; a home office improvement stipend; annual education and wellness stipends; regular company events; and healthy lunches daily.

As part of the interview process, candidates complete a brief AI-focused exercise or discussion about how they think about, design, and use AI to drive impact.