Data Science Tech Lead Manager – Core Product

Data Science Tech Lead Manager – Core Product

Requirements

• 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 minimum 3+ years of hands-on management experience with a team of 5+.
• 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.

Responsibilities

• 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.
• Explore how Glean’s search and generative AI products should intersect.
• Explore different product modalities like web, mobile and desktop apps, as well as experiences where Glean’s embedded into other products like an internal portal or another B2B SaaS product like Slack.
• Explore how unstructured data in documents, structured data and data outside of an organization should come together.
• Look into the knowledge worker as a potential creator of generative AI experiences for others around her, rather than a mere consumer of these experiences.
• Think about empowering Glean’s customers to reign in the proliferated set of AI agents around them for maximum value, whether or not they are created by or on Glean.
• Use product analytics to enhance a user and customer’s experience.
• Present important strategic insights & wins to executive leadership.

Preferred Qualifications

• 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 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.