Staff Data Scientist

Chegg Chegg · Consumer · Remote

Staff Data Scientist role focused on building an organizational intelligence capability to shape company decisions, measure AI transformation, and establish trusted business metrics. This role will design measurement systems, synthesis, and learning loops, partnering with leadership and various functions.

What you'd actually do

  1. Design and run the analytical architecture behind Monthly and Quarterly Business Reviews, ensuring they lead to decisions rather than reporting theatre.
  2. Create the company-level performance narrative by synthesising signals across B2C, B2B, Product, Lifecycle, Commercial, Finance, and AI initiatives.
  3. Build and operationalise the framework used to measure organisational and AI transformation, including efficiency, effectiveness, and human impact.
  4. Own canonical definitions for the company’s most important business metrics and create a robust process for resolving definition disputes across teams.
  5. Design maturity models and business learning loops that help Busuu improve how it makes decisions over time.

Skills

Required

  • 8+ years of experience in data science, analytics, business intelligence, strategy, consulting, or a similar function in a scaled digital, SaaS, consumer tech, subscription, or EdTech business.
  • Strong experience translating analysis into business decisions, preferably with exposure to executive or leadership-level reporting.
  • Experience designing performance frameworks, KPI systems, company scorecards, business review processes, or equivalent decision-support systems.
  • Strong SQL skills and confidence working directly with complex datasets.
  • Ability to move fluidly between hands-on analytical work and high-level executive communication.
  • Experience influencing senior stakeholders across functions such as Product, Finance, Commercial, Marketing, Operations, Engineering, or Data.
  • Strong commercial judgment, including understanding of metrics such as bookings, retention

What the JD emphasized

  • AI transformation
  • AI governance
  • measure organisational and AI transformation