Senior/Staff Applied Scientist
AI in this role
Collaborate with product and engineering teams on applied science and online A/B experimentation to advance enterprise Work AI systems.
- 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.
- 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.
- This role is hybrid (4 days a week in our San Francisco office)
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How we rate this
Senior/Staff Applied Scientist at Glean Work rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where applied science was part of your work. What did you do?
- Tell me about a project where a b testing was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Agents, Applied Science, A B Testing, Machine Learning, and Data Science. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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