Stripe16 дней назад
Специалист по борьбе с мошенничеством
Зарплата не указана
РЫНОК
16 250 ₽медиана по профессии
Data Scientist · 212 вакансий с указанной зарплатой
5 000половина предложений: 13 084–21 768120 000
Работодатель не указал зарплату — сравните с рынком сами.
LOCATION
Обязанности
- 01Monitor portfolio to identify, mitigate and predict risky behavior that could result in losses for Stripe, our users, and the financial ecosystem
- 02Collaborate with internal partners like Product, Engineering, Data Science, Risk Partnerships, and Operations, to tailor fraud risk management techniques to various products and payment methods across the globe
- 03Continually evaluate products for gaps and propose risk controls to enhance the product while enabling growth
- 04Scale risk processes to cover a large and complex landscape of fraud risks. Effectively design, outsource and automate manual/repetitive workflows
- 05Work with Stripe users to educate them and guide them on how to prevent potential fraud risks to their business
- 06Effectively and clearly communicate with other Stripes, Stripe's users, and Stripe's financial and regulatory partners
Требования
- 015+ years of relevant experience, preferably in Financial Services, Payments or FinTech
- 02Curiosity and passion for risk management - you dig into anomalies and solve root causes
- 03Decisiveness and openness to learning, with comfort making high-impact calls daily
- 04Data-driven judgment - skilled at using quantitative analysis to drive and defend decisions
- 05Empathy for early-stage businesses and the ability to balance enforcement with user experience
- 06Strong analytical skills, including the ability to frame complex tradeoffs through data and visualization
- 07Advanced SQL skills with hands-on experience in business environments
- 08Proven ability to collaborate and execute cross-functionally with Engineering, Product, Data Science, and Operations
- 09Excellent written and verbal communication skills, with the ability to convey complex ideas clearly across teams
- 10Holistic thinking and the ability to build scaled processes that bridge systemic gaps
- 11Track record of deriving actionable insights from complex problem spaces and influencing product direction
- 12Ownership mentality and the ability to lead without formal authority
- 13Proficient with AI tools to accelerate productivity and process automation