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Fraud Analyst

Fraud Analyst

KalshiNew York, NY, United States
Hace 16 horas
Tipo de contrato
  • A tiempo completo
Descripción del trabajo

Kalshi is defining a new category

Kalshi has defined a new category : prediction markets. Kalshi allows people to trade on the outcome of any events and turn any question about the future into a financial asset. Kalshi fought for years and legalized prediction markets in the US for the first time in history. Kalshi is currently the fastest growing financial market in America, and has thousands of markets across politics, economics, financials, weather, tech, AI, culture and more.

We believe prediction markets have the potential to be the largest financial market because they turn anything into a financial position.

  • Our vision : well... build the largest financial market on the planet.
  • Our mission : bring more truth to the world through the power of markets.

Building a new category is hard... like really hard. But it's beautiful and deeply fulfilling. Our culture is simple : we hire really talented people, work really hard, and enjoy the climb. We are looking for ambitious and exceptional people to join our (relatively small) team to help us build the next generation of financial markets.

About the Role

As a Fraud Analyst at Kalshi, you'll help protect our users and platform by detecting, investigating, and preventing fraud. You'll analyze transactional and behavioral data, monitor fraud signals, and partner with teams across product, data, and compliance to strengthen our defenses while keeping the user experience smooth. You'll manage a high volume of fraud cases and tickets, performing day-to-day reviews and investigations to ensure fast and accurate resolution.

This role is a great fit for someone who's analytical, detail-oriented, and excited to dig into data to uncover patterns and stop fraud before it happens.

What You'll Do

  • Monitor real-time transactions, account activity, and behavioral patterns to identify potential fraud or abuse.
  • Investigate suspicious activity, document findings, and recommend next steps for remediation.
  • Define, test, and optimize fraud detection rules to improve accuracy and reduce false positives.
  • Analyze fraud data to identify trends and propose new rules or controls.
  • Partner with engineering, product, and compliance to improve detection systems and automate workflows.
  • Support incident response, escalations, and fraud investigations.
  • Build and maintain dashboards and reports to track fraud health metrics.
  • Stay current on evolving fraud techniques, payment risks, and industry best practices.
  • What We're Looking For

  • 2+ years of experience in fraud prevention, payments risk, or financial crime investigation at a fintech, trading, or marketplace company.
  • Strong analytical skills with proficiency in SQL / Python
  • Familiarity with fraud typologies such as account takeover, identity fraud, transaction fraud, and chargebacks.
  • Comfortable analyzing large datasets and working cross-functionally to solve problems.
  • Excellent attention to detail and communication skills.
  • Curiosity and initiative to dig deep into ambiguous cases and drive improvements.
  • Experience with ACH, card payments, or digital wallets, and knowledge of AML / KYC frameworks.
  • Commitment to Equal Opportunity

    Kalshi is committed to creating a culture of inclusion and belonging, and we are proud to be an equal opportunity employer. We believe it is our collective responsibility to uphold these values and encourage candidates from all backgrounds to join us in our mission. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, veteran status, age, or any other protected characteristic per federal, state, or local law. If you are passionate about what you do and want to use your talents to support our mission and values, we'd love to hear from you.

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