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, Rubrik, Uber, Intercom, Pinterest, Palantir, and others.
About the 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 in our IND office.
At Glean, data scientists collaborate with engineering, product management and other functions like customer success in our IND and Silicon Valley offices to
- build data products and infrastructure to measure the performance of and assist decisions to improve AI powered search and assistant products for knowledge workers, e.g. KPI definitions, and data foundations & dashboards to track them
- proactively contribute to strategic decision-making by sharing insights and learnings at all levels of the organization, e.g. identify opportunities to improve the quality and user base of a product.
- Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into defining what it means for a user to be satisfied with a search product.
- Insights is a product that informs administrators at Glean’s customers about how Glean is used at their company and how else Glean could deliver more value to them. You’ll collaborate with engineers, product managers and customer success managers to improve this product’s usability and comprehensivity while retaining its accuracy. You’ll collaborate with representatives from some customers to define and implement additional more tailored ways of measuring how Glean is adding value to them. At times, you’ll contribute to these measurements via deep dive custom analyses from your end.
- Working with engineering and product management teams, you’ll refine, measure and generate strategies to improve KPIs for the autocomplete feature for our search product. You’ll help identify opportunities for these products to be more compelling and performant for its users to ultimately make Glean mission-critical for every knowledge worker.
- Working with engineering teams, you’ll help monitor and identify opportunities to improve the reliability and cost-efficiency of Glean’s infrastructure, e.g. cloud costs, outages, stability of data sources that power Glean search.
- You have a Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field
- You have 4+ years of industry experience (2+ for Masters degree holders, 4+ for PhD degree holders) with demonstrated
- 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 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 proficient in Python.
You are a particularly good fit if:
- You have experience in B2B SaaS, especially in a customer-facing way.
- You have experience with remote work across large time zone differences.
- 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.
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.
