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 growth and engagement.

The Growth tiger team’s mandate is to grow Glean’s user base and deepen Glean’s usage by existing users. This team involves product management, engineering, data science and design roles, and works across other product teams, as well as customer success management (CSM) teams. As the data science lead of this tiger team, you would:

• Define KPIs, build foundational data assets, and develop visualizations to monitor Glean’s growth across different stages of the user journey. Use data-driven insights to prioritize growth opportunities and influence the roadmaps of growth, and product teams.
• Partner closely with product management, engineering, and CSM teams to enhance user interactions and experiences that drive growth, iterating on our KPIs, dashboards, and measurement techniques. Identify key drivers of user retention and engagement, enabling data-informed improvements to increase Glean’s value proposition and support CSM teams in scaling customer insights and impact.
• Partner with Customer Success Management (CSM) teams to understand customer behaviors and needs at scale, enabling them to proactively engage with customers and improve product value realization.
• In some of these initiatives, you’d be the directly responsible individual (DRI) and interface with executive leadership to represent the growth tiger team and communicate its findings & results.
• You’d be among the main drivers of the growth team’s quarterly and annual strategy.
• Tech-lead other growth data scientists. Upon strong performance as an IC leader, this role would evolve into a tech-lead manager role, where you’d be responsible for hiring and mentoring more growth data scientists.
• Make sure growth data science collaborates cohesively with other data science pods as well as other data roles like data engineering, business intelligence and applied science. 

Minimum qualifications:

• You have a Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field.
• You have 8+ years of industry experience as a data scientist. For PhD degree holders, the minimum years of experience as a data scientist is 6 years.
• You have strong business sense, and 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 are strong at statistics. You have experience in applying these skills into tangible improvements in products, internal tools and processes using A/B testing and non-experimental methods.
• You are proficient in Python. 
• You are familiar with BI visualization tools such as Sigma, Metabase, Tableau or Looker.
• You are concise and precise in written and verbal communication. Technical documentation is your strong suit. 

You are a particularly good fit if:

• You have experience working with Growth teams.
• You have experience in B2B SaaS.
• You have experience in tech lead management.
• You have experience in executive communication. 
• You have experience working with collaborators across large time zone differences.
• You are passionate about using AI to improve the productivity of data teams as well as non-data professionals trying to derive more value from 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 - 250,000 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.