Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
BI
Communication @ 6
Data Engineering
Data Visualization @ 6
Payments
Python @ 3
R @ 3
Security
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Who We Are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Stripe's mission is to increase the GDP of the internet.
About the Team
The People Analytics team improves Stripe's performance by collecting data, measuring critical constructs, and generating insights that help Stripe attract, develop, and retain its employees. The team includes professionals from consulting, HR, and data-focused disciplines who use science and data to deliver precise, high-value outputs.
Responsibilities
- Serve as the primary analytics partner and single point of contact for People Partners and senior business leaders supporting Stripe's International organization.
- Develop and present comprehensive analyses that shape how leaders understand and act on their organizations, including urgent ad hoc requests.
- Design, build, and maintain analytics products and self-service tooling through Visier and AI-powered solutions.
- Lead backend Visier platform administration, including metric and dimension configuration, data hygiene, security, and report design governance.
- Partner with data engineering to identify and execute improvements to the workforce data ecosystem.
- Collaborate with People Research and Insights, People Partners, and the business to identify and deliver high-impact work.
- Lead projects such as organizational health analysis, team size and spans, talent density, recruiting productivity, and geographic strategies.
Requirements
Minimum Requirements
- 5+ years of experience in management consulting, people analytics, or a related analytical role, inside or outside of HR.
- Demonstrated ability to operate as a business partner and work directly with senior stakeholders as a single point of contact.
- Strong data visualization and communication skills, including the ability to translate complex findings into clear narratives for audiences such as senior leaders.
- Working knowledge of Visier or a comparable business intelligence platform; Visier experience is strongly preferred.
- Hands-on experience using AI platforms such as Anthropic, OpenAI, or Google to develop tooling and accelerate analytical workflows.
- Experience with human capital benchmarking and target setting.
- Ability to work comfortably with ambiguity and competing priorities while delivering high-quality work at pace.
Preferred Qualifications
- Experience supporting international or multi-site organizations.
- Experience across the full analytics project lifecycle, from requirements gathering through deployment.
- A bias toward automation, self-service enablement, and building for scale.
- Experience with a scripting language such as Python or R.
- Knowledge of current best practices, research, and case studies in people analytics and workforce measurement.
- Ability to bring structure to ambiguity.
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