Why This Job is Featured on The SaaS Jobs
Why this Role is Featured on The SaaS Jobs
Applied science roles in B2B SaaS increasingly sit at the center of product decision-making, and this position is notable for anchoring that influence in measurement infrastructure. The remit spans experimentation methodology, platform development, and evaluation of LLM-driven features, reflecting how modern SaaS products are blending classic growth analytics with AI capability assessment. The hybrid Bay Area setup also signals close partnership with product and engineering on production systems rather than isolated research.
From a SaaS career perspective, owning A/B experimentation and evaluation tooling builds durable leverage. These systems become shared internal platforms used across product domains, which forces strong thinking on metrics, guardrails, statistical rigor, and usability for non-specialists. Experience translating stakeholder needs into scalable workflows, plus shipping code that others depend on, transfers well across SaaS companies investing in experimentation maturity and AI feature reliability.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Role:
Glean is building a world-class Data Organization composed of product data science, applied science, data engineering and business intelligence groups. This is an applied science role based in our Palo Alto or San Francisco office.
You will:
- Collaborate with product data science and engineering teams to identify techniques, tooling and process improvements in online A/B experimentation to assist rigorous decision making across all relevant product domains.
- Develop and maintain our A/B experimentation platform based on stakeholder feedback
- Write code or identify vendors to deploy these techniques to production in a scalable manner that’s easy to use by engineering, product data science, product management and design teams
- Conduct end to end evaluation of various hero use cases like document/URL uploads, including evaluation set generation, coming up with evaluation criteria and methods to interpret the results.
- Break down end to end evaluations into more granular evaluation of various tasks & skills including but not limited to content summarization/analysis/generation, multi-step reasoning & strategizing, tool selection & use, coding & system design.
- Design, develop and own best practices, tools and processes across various evaluation problems, e.g. query intent classification, standardizing the use of best statistical principles to handle LLM stochasticity, industry benchmarking.
About you:
- You have 5+ years of experience as a Masters degree holder, 3+ as a PhD degree holders (Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field)
- You’re strong in statistics and/or machine learning. You have experience in applying these skills into tangible improvements in products, internal tools, and processes in a pragmatic way that puts business urgencies first.
- You are very proficient in Python, e.g. proficient enough to maintain an internal source-controlled library used by dozens of others.
- You are concise and precise in written and verbal communication. Technical documentation is your strong suit.
- You are proficient in SQL and the modern data stack (e.g. source-controlled dbt pipelines for ETL/ELT).
- You are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.
- You have experience in B2B SaaS.
- You have experience working on ranking, developing, and maintaining A/B experimentation platforms and/or ML measurement problems.
- You are passionate about using AI to improve the productivity of data teams as well as non-data professionals trying to derive more value of their company’s data.
Location:
- This role is hybrid (3-4 days a week in one of our SF Bay Area offices)
Compensation & Benefits:
The standard base salary range for this position is $175,000 - $230,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
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