Data Science Lead, Glean

• 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

Desirable

• 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