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Transaction Fraud Strategy Analyst

1 day ago

Toronto, Ontario, Canada Stripe Full time
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

Stripe's Fraud Risk Team is committed to minimizing Stripe's financial losses from fraud attacks. The Transaction Fraud Team is responsible for building and implementing strategies that scalably reduce risk for Stripe and preserve a healthy payment and financial ecosystem, while creating positive experiences for users.

What you'll do

As a Transaction Fraud Strategy Analyst on the Transaction Fraud team, you will be directly responsible for preventing, detecting and mitigating Transaction Fraud at Stripe. You will enable safer payments for our users and help Stripe manage payments risks intelligently. The stakes are high, and you will be up against ever-evolving challenges. You will face some of the most complex and dynamic problems at the company, and the nature of your work will evolve rapidly to combat new and more sophisticated challenges to Stripe's payments integrity.

Responsibilities
  • Monitor portfolio and transactions to identify, mitigate and predict risky behavior that could result in losses for Stripe, our users, and the payment ecosystem
  • Collaborating with internal partners like Product, Engineering, Data Science, Risk Partnerships, and Operations, to tailor fraud risk management techniques to various products, payment methods across the globe
  • Continually evaluate product for gaps and propose risk controls to enhance the product while enabling growth
  • Scale risk processes to cover an increasingly large and complex landscape of payments risks and effectively design and outsource manual/repetitive workflows
  • Work with Stripe users to educate them about and help prevent potential risks to their business
  • Challenge the payments industry status quo to help enable innovative businesses to flourish online
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. The preferred qualifications are a bonus, not a requirement.

Minimum requirements
  • 5+ years of relevant professional experience
  • Curiosity and passion for risk management: if something seems off, you want to investigate what's going on and solve root problems
  • Decisiveness, yet open to learning: you will make many critical decisions every day impacting large numbers of merchants
  • Willingness to make these difficult decisions and quickly learn and iterate from these experiences - you are skilled at using data to drive decisions
  • Understanding and empathy for the challenges of setting up a new business - you will thoughtfully balance scaled enforcement decisions with user experience
  • Strong analytical skills - you are passionate about data analysis and can frame business decisions and tradeoffs effectively through quantitative analysis and visualization
  • Advanced SQL skills and experience in applying these skills in business environments
  • Demonstrated experience working in a cross-collaborative environment, mainly with Engineering, Product, and Data Science partners 
  • Excellent communication skills and knows how to be a team player - you are able to convey complex ideas succinctly and work effectively across teams
  • Ability to think holistically and build out processes to bridge gaps in the system
Preferred qualifications 
  • Expertise with quantitative tools such as Python, R, etc
  • Experience with payments, risk, or trust & safety
  • Experience working with product teams
  • Experience working with machine learning teams
  • Experience working in fast-paced and rapidly changing start-up environments