Podcast
How to Hire, Manage, and Grow a Data Science Team in B2B SaaS
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How to Hire, Manage, and Grow a Data Science Team in B2B SaaS
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Episode Overview
How do you hire, manage, and grow a high-impact data science team inside a B2B SaaS company? In this episode, Katie Bauer — Head of Data at GlossGenius and former data leader at Twitter and Reddit — walks through practical career frameworks and team-building strategies for product analysts, analytics engineers, marketing scientists, and data scientists. Katie traces her own trajectory from linguistics to analytics and explains what “craft” looks like in analytics: maintainability, documentation, and peer review..
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Chapter Summary
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- 0:00 - Podcast Introduction
- 1:33 - Introduction: Episode focus on data science career development (Katie Bauer)
- 2:27 - Career trajectory: linguistics to data science; Reddit and Twitter experience
- 4:36 - GlossGenius product and head of data responsibilities (B2B SaaS)
- 6:22 - Current hiring needs: product analysts, analytics engineers, marketing scientists
- 7:08 - Data scientist role: broad definition and varied responsibilities
- 8:33 - Data science manager: building teams, matrix orgs, and cross-functional work
- 11:58 - Craft quality: maintainability, documentation, peer review for analytics
- 15:12 - Career framework: junior vs senior and the “terminal” career level
- 18:50 - Senior growth: abstraction, leadership exposure, and delegation
- 25:54 - IC vs management: trying people leadership and the IC–manager pendulum
- 30:10 - Managing juniors: mentorship, skills training, and project-based learning
- 34:16 - Stakeholder conversations: talking to PMs and senior leaders (prep & questions)
- 39:02 - Junior development: practice, exposure, and avoiding early specialization
- 40:12 - Hiring juniors: build vs buy, long-term org benefits, and succession
- 44:39 - Hiring managers: evaluation criteria for data science manager roles
- 47:21 - Strategy assessment: case studies, trade-offs, and measurement in interviews
- 50:21 - Entry-level hiring tips: standing out, outreach, and interview preparation
- 52:43 - Onboarding first month: proactive communication and asking for help
- 54:11 - Support mechanisms: regular check-ins, rubber-duck channels, async help
- 56:20 - Head of data challenges: prioritization, data literacy, and culture building
- 59:09 - Closing advice: careers as direction and guiding team growth