About Glean
We’re on a mission to bring people the knowledge they need to make a difference in the world.
Glean was founded by a seasoned team of former Google search and Facebook engineers, who wondered why we don’t have an easier way of finding what we need at work. In our personal lives, we have tools to help us find pretty much whatever we need. Why don’t we have that at work? And that was the beginning of Glean.
Glean searches across all your company’s apps to help you find exactly what you need and discover the things you should know. 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.
Data Scientist Role:
Glean is building a world-class data science org. This is an early-hire, full-stack and hands-on data scientist role spanning product analytics, applied science and building data foundations.
- Analytics:
- You’ll refine, measure and generate strategies to improve KPIs for a wide range of knowledge work products like search, generative AI experiences, knowledge management and workplace productivity.
- You’ll help measure and improve the efficiency of our ranking and overall infrastructure.
- You’ll define, measure and improve the effectiveness of our marketing initiatives to generate more and better sales leads. You’ll equip sales teams with quantitative insights to close more and bigger deals. You’ll help customer success teams measure and improve how they roll out Glean into customer firms faster, with more adoption and greater partner satisfaction.
- Applied science:
- You’ll identify and build our tools, techniques and processes to improve the way A/B experimentation is done across the company
- You’ll identify and improve tools, techniques and processes in the measurement of the efficacy of ML models used in ranking and various generative-AI products.
- You’ll identify and execute on new opportunities to introduce more statistical sophistication into other decision making across the company, e.g. metric forecasting for improved KPI targets, predictive models for more proactive user churn prevention, sophisticated metric alerting systems.
- Data foundations:
- Co-design and improve the logging for our products to facilitate improved analytics and applied science techniques
- Build pipelines based on these logs to empower the analytics and applied science applications.
- Develop and execute on a holistic perspective of Glean’s data model to help realize synergies across various product surfaces and teams across the company as the company scales up.
You’ll have plenty of technical leadership opportunities as the data science team grows and as you collaborate with data-savvy cross-functional collaborators. You’ll flex your people leadership muscles by collaborating with a very broad spectrum of partners ranging from Marketing, Sales and Customer Success to Product Management and Engineering. You’ll have a defining say in Glean’s data culture and how data science at Glean delivers value across analytics, applied science and/or data foundations.
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 8+ years of industry experience (6+ for Masters degree holders, 4+ for PhD degree holders) with demonstrated
- independence & self-motivation in a large & vague scope
- balance between scrappy execution to drive more business value sooner and longer term/bigger picture perspectives
- curiosity & ability to learn new skills/tools fast
- ability to communicate very effectively with collaborators with very different roles
- 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 for analytics engineering / pipelining, Fivetran and Census for ETL/ELT)
- You are proficient in Python or R. 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 a particularly good fit if:
- You have experience in B2B SaaS
- You have experience in similar products on ranking, generative AI and knowledge work.
- You have tech-lead management experience.
- You have experience with remote work across large time zone differences.
