Job description
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. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the team
As Stripe continues to develop innovative products that serve businesses of all sizes around the world, risk will increase in complexity and scale. The Onboarding and Compliance Strategy organization protects and advances Stripe’s business, brand, and mission by building and deploying industry-leading standards and programs that instill user, regulator, and partner trust in Stripe while enabling business growth. This role will be focused on developing processes, solutions, and product controls by completing analyses, experiments, and simulations in partnership with partners across Data Science, Product, and Engineering.
What you’ll do
As a member of this team, you will have a deep understanding of Stripe’s onboarding and compliance policies, systems, and controls. We are looking for an experienced risk management professional to join the group and help drive user compliance efforts. You will leverage data and work with technical teams to build analytical tools and frameworks to empower the team set as well as inform control development in areas such as Know Your Customer (KYC), Know Your Business (KYB), and Financial Crimes / Anti-Money Laundering (AML). We are looking for someone who is passionate about navigating ambiguity, enabling business growth while balancing risk, and is skilled at identifying ways to improve user experience.
Responsibilities
- Work in collaboration to design and drive user onboarding and compliance strategy
- Build relationship and partner with stakeholders across Data Science, Product, Engineering, and Ops
- Build expertise and deep know-how around Stripe’s policies, standards, and user requirements, as well as risk capabilities and tools
- Leverage data and quantitative analysis to build optimal solutions, balancing risk and user experience
- Enable user onboarding to safely grow at scale, continuously optimizing for efficiency and effectiveness, and staying hyper focused on a positive user experience
Who you are
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply.
Minimum requirements
- 10+ years of professional experience, preferably in financial or tech sectors, particularly within a risk management or revenue enablement function
- 10+ years experience in a role with an emphasis on data analysis and/or a strong technical background. You have worked closely with engineers and data analysts to build systems, collect business requirements, and/or deliver insights
- Required proficiency in SQL
- Expertise in Know Your Customer (KYC), Know Your Business (KYB), Financial Crimes / Anti-Money Laundering (AML), and user onboarding standards and controls
- An analytical approach to decision-making. You are analytical, objective and skilled at using metrics to drive decisions, set goals, and evaluate performance
- Experience communicating to all levels of management. Including strong writing skills with experience writing strategy documents, one-page project updates, and proposals
- Strong collaboration and relationship-building skills, with an ability to influence stakeholders across organizations and border
- A results- and action-oriented mindset and the ability to lead and motivate others
- The ability to take ownership, be accountable, and drive towards ambitious goals
- Comfort operating in an ambiguous and quickly changing environment with shifting priorities (this is a must!)
- Experience working in payments and/or tech industries
- Preferred experience coding, ML algorithms/predictive modeling
