The opportunity
The APAC Payments TechOps team ensures the accuracy of financial data flowing through Stripe's payment infrastructure, manages aging balances, maintains compliance with partner and regulatory requirements, and builds tooling to detect and resolve data quality issues at scale.…
What you'll do
Analyze financial data by writing queries and examining data quality,: reconciliation accuracy, or cost structures across Stripe's payment flows
Write code or build tooling that will be used in production and has: meaningful impact to Stripe's payment operations
Give and receive technical feedback through code reviews, data model discussions, or analysis walkthroughs
Collaborate with engineers, product managers, and finance stakeholders to: seek and incorporate feedback on your work
Learn quickly by asking great questions, by working with your intern manager: and teammates effectively, and by communicating the status of your work clearly
What they're looking for
- Ambitious builder: You’re energized by building solutions without clear precedent and solving problems with far-reaching consequences. Successful Stripes are deeply curious, and prefer the joy of discovery to the comfort of certainty.
- Rigorous thinker: You appreciate that things worth doing are rarely simple. You enjoy working on problems that have never been tackled before.
- Adaptable problem solver: You adapt quickly and treat obstacles as opportunities. At Stripe we embrace kindness while encouraging Stripes to take measured risks and act boldly, even in the absence of consensus.
- A strong fundamental understanding of quantitative analysis through pursuit: of a Bachelor's, Master's, or PhD degree in computer science, data science, finance, economics, information systems, or a related discipline
- Some experience and familiarity with programming or data analysis, either: through side projects or coursework. We work mostly in SQL, Python, and Ruby. We believe new programming languages can be learned if the fundamentals and general knowledge are present
- Experience from previous internships or other multi-person projects,: including open source contributions, that demonstrate evaluating and receiving feedback from mentors, peers, and stakeholders
- Ability to learn unfamiliar systems and form an understanding of those: systems, through independent research and working with a mentor and subject matter experts
- At least 2 years of university education, or equivalent work experience
