Toa Payoh - Data Science Manager, Analytics - Supply Chain Products

apartmentFACEBOOK SINGAPORE PTE. LTD. placeToa Payoh descriptionPermanent calendar_month 
Supply Chain Products is crafting the world's best product suite to redefine how the company runs its operations and infrastructure, empowering people at Meta to reach unparalleled levels of productivity. Our tooling supports spend optimization, data center supply chain, Commerce, and protecting Meta from reputation and regulatory risks.
Ideally, you will be excited about working collaboratively with a diverse and motivated team of self-starters. We work closely with cross-functional partners including engineers, product managers, business partners, and designers to ensure our products achieve their promises in a measurable way.

You will lead and grow a team of high-performing analytics professionals, partner with supply chain and business leaders across the broader Meta ecosystem, and hold a high bar for analytics work. As this is a high visibility role scoped for growth, you will be experienced in communicating with peers & leaders at all levels.

Responsibilities
  • Maintain a high bar in terms of product thinking and analytical depth for your team through selective hiring and mentorship.
  • Set goals and metrics to guide and prioritize growth product roadmaps.
  • Conduct analytics studies to identify new product opportunities and shape product strategy.
  • Size opportunities to ensure product teams are working on the most impactful projects.
  • Partner and heavily contribute to major analytical and product initiatives across Enterprise Products (Supply Chain, Financial, Knowledge, and Commerce tools).
  • Serve as part of the core leadership team for Enterprise Products with direct accountability for the success and health of this organization.
Minimum Qualifications
  • Bachelors in a quantitative field (Physics, Economics, Computer Science, Engineering, Mathematics, Psychology).
  • 5+ years of experience in Product Data Science and/or Growth Analytics, including in depth experience with experimentation.
  • 2+ years experience in building high-performing data science and analytics teams.
  • Working knowledge of predictive modeling, machine learning, and experimentation/causal inference methods.
Preferred Qualifications
  • Proven judgment in balancing practical business needs and scientific rigor.
  • Experience communicating effectively and connecting with and influencing a broad spectrum of audiences.
  • Proven experience forming partnerships with and influencing cross-functional leaders in engineering, product, design, research, etc.
  • Masters or Ph.D. in a quantitative field (Physics, Economics, Computer Science, Engineering, Mathematics, Psychology).
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world.

Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

placeToa Payoh
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