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.
If you are up to it, this role would span a large product portfolio that aims to make Glean mission critical and delightful for the knowledge worker (i.e. the user) and the firm she works at (i.e. the customer): It explores how Glean’s search and generative AI products should intersect. It explores different product modalities like web, mobile and desktop apps, as well as experiences where Glean’s embedded into other internal and external services a customer uses. It explores how unstructured data in documents, structured data and data outside of an organization should come together.
It looks at the knowledge worker as a potential creator of generative AI experiences for others around her, rather than a mere consumer of these experiences. It empathizes knowledge workers in specific job function verticals. It seeks to empower Glean’s customers to reign in the proliferated set of AI agents around them for maximum value, whether or not they are created by Glean. At the intersection of all these domains is an obsession about a user and customer’s experience. Combined with an enterprise-grade & highly performant AI, such magical experience is the prerequisite for making Glean grow into over 1B knowledge workers out there.This role presents a lot leadership opportunities including:
- Being the main data science point of contact for multiple high-profile initiatives to collaborate with various ENG, product management and design XFNs.
- Tech-leading other data scientists working in similar domains.
- If you deliver strong results as an IC leader, this role would also evolve into tech lead management as well. You’ll always stay hands on though, just all Gleanies.
- Making sure that your data science pod works cohesively with other data science pods as well as other data roles like data engineering, business intelligence and applied science.
- Presenting important strategic insights & wins to executive leadership
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 required 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 familiar with BI visualization tools such as Sigma, Metabase, Tableau or Looker.
- You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).
- You are proficient in Python.
- 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 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 multiple product teams at once, especially in the enterprise AI space.
- 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 have experience 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.
