About Glean

We’re on a mission to make knowledge work faster and more humane. We believe that AI will fundamentally transform how people work. In the future, everyone will work in tandem with expert AI assistants who find knowledge, create and synthesize information, and execute work. These assistants will free people up to focus on the higher-level, creative aspects of their work.

We’re building a system of intelligence for every company in the world. On the surface, you can think of it as Google + ChatGPT for the enterprise. Under the hood, our platform is the connective tissue between AI and knowledge. It brings all of a company’s knowledge together, understands it at a deep level, provides industry-leading search relevance over it, and connects it to generative AI agents and applications.

Glean was founded by a seasoned team of former Google search and Facebook engineers who saw a need in the enterprise space for their technical depth and passion for AI. We’re a diverse team of curious and creative people who want to help each other get big things done—so we can help other teams do the same. 

We're backed by some of the Valley's leading venture capitalists—including Sequoia, Kleiner Perkins, Lightspeed, and General Catalyst—and have assembled a world-class team with senior leadership experience at Google, Slack, Facebook, Dropbox, LinkedIn, Stripe, Rubrik, Uber, Intercom, Pinterest, Palantir, and others.

Role

Glean is building a world-class Data Organization composed of data science, applied science, data engineering and business intelligence groups. This is a data science role based in our Palo Alto headquarters.

At Glean, data scientists collaborate with engineering, product management and design to

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.
• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.
• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user churn & retention.

This specific role will address one or more of the following business domains:

• Define KPIs, create data foundations, build visualizations and devise techniques to measure the efficacy of Glean’s world-leading document indexing, retrieval and ranking infrastructure, which powers its search and LLM-powered products. Conduct rigorous empirical analyses and influence ML ENG & ENG to improve this infrastructure.
• Collaborate with product management and product ENG teams to improve the way Glean measures interactions with its Search product, iterating on our KPIs, data foundations, dashboards and measurement techniques accordingly. Identifying opportunities and influencing ENG, design and product management XFNs to improve value-add of a user’s experience with Search vis a vis other LLM-based and general knowledge management products Glean offers.

You will thrive at this role if:

• You have a Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field.
• You have 6+ years of industry experience (4+ for Masters degree holders, 3+ for PhD degree holders). 
• You are concise and precise in written and verbal communication. Technical documentation is your strong suit. 
• You are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.
• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT). 
• You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.
• 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.
• You are proficient in Python. 

You are a particularly good fit if:

• You have experience in B2B SaaS.
• You have experience with remote work across large time zone differences.
• You have experience working on ranking 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

Benefits

• Competitive compensation
• Medical, Vision and Dental coverage
• Flexible work environment and time-off policy
• 401k
• Company events
• A home office improvement stipend when you first join
• Annual education stipend
• Wellness stipend
• Healthy lunches and dinners provided daily

For California based applicants: 

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 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.