Head of Fraud

Head of Fraud & Risk at Nova Build the future of payments with AI, Pix & Open Finance Hands-on, data-driven fraud leader. 7+ years in fraud prevention or credit risk at fintechs, acquirers, issuers or fraud-prevention companies (e.g. Nubank, Stone, Stripe, Mercado Pago, Feedzai). Strong SQL/data background required. Type: Full-Time Language: English

Location:
São Paulo, Brazil (Hybrid) Reports to: CEO The Company Nova is building a new generation payment network (i.e. reinventing Visa/Mastercard) using AI on top of Pix and Open Finance. Its first product is a B2C digital wallet that works as an infrastructure bridge between traditional credit cards and Pix. It lets consumers use their existing credit card limits anywhere, even to pay Pix and Boletos in installments. The company was founded by an elite team of fintech veterans and has been backed by top-tier venture capital investors (Monashees, Canary, Canaan and Propel) since its inception. Nova recently raised a large Series A and is now assembling a small team of exceptional, experienced professionals to build, launch and grow its next generation of products. The Role We are looking for an exceptional fraud and risk leader to own Nova's fraud and risk P&L end to end: keeping fraud losses and chargebacks low while maximizing approval rates. You will work closely with the founders, Engineering and Data Science to define policies, oversee our proprietary models, manage vendors and measure everything with data.

Key responsibilities
include: Risk Management
• User Risk/Reward Assessment: policy definition, results monitoring & reporting, vendor management (incl. cost), proprietary model oversight (Data Engineering + Data Science)
• Card Risk/Reward Assessment: policy definition, results monitoring & reporting, vendor management (incl. cost), proprietary model oversight (Data Engineering + Data Science)
• Transaction Risk/Reward Assessment: policy definition, results monitoring & reporting, vendor management (incl. cost), proprietary model oversight (Data Engineering + Data Science) Fraud Operations
• Account Security
• Case Management
• Chargeback Management
• Disputes & Recoveries Onboarding & Identity Fraud (KYC)
• Info Collection, Background Check & Identity Check
• Policy Definition
• Results Monitoring & Reporting
• Vendor Management (incl. cost) The Qualifications Required
• 7+ years in fraud prevention, credit risk or risk analytics, including 3+ years leading teams
• Experience at high-performing fintechs, financial services companies and/or startups
• Bachelor's (or equivalent) degree in Engineering, Economics, Statistics, Mathematics, Computer Science or another quantitative field
• Hands-on with SQL (Python a plus); comfortable building your own analyses and challenging model results (precision/recall, approval vs. loss trade-offs)
• Daily use of AI in your work (research, data analysis, spec'ing and/or prototyping)
• Analytical and organized mind: structured thinking, comfortable with numbers, detail oriented Preferred
• Experience launching products (0 → 1)
• Graduated from top schools and/or with top grades
• Took part in and/or won competitions, or received work-related awards
• Active leader in the community: published articles, given lectures, etc.
• Other demonstrable proof of ambition, intelligence and/or resilience This is a quantitative, data-driven role. Profiles focused primarily on legal, regulatory compliance or AML are not a fit. The Target Companies Candidates with at least 2 years of full-time experience at the companies below will be prioritized: Strong Local Fintechs:
• Acquirers: Cloudwalk, Stone, PagBank, Hash
• Card Processors: Pismo, Stark, Pomelo
• Card Issuers: Nubank, Cora, Clara, PicPay, RecargaPay
• Other: Belvo, Klavi, Iniciador, Magie, Jota, Barte, Pagaleve, Ume, Creditas
• Strong Global Fintechs: Stripe, Plaid, Melio, Brex, Wise, Affirm, Klarna, AfterPay, Marqeta, Chime
• Strong Financial Services: XP, Willbank, Inter, C6, Mercado Pago, Avenue, Itaú
• Strong Local Start-Ups: Wildlife, QuintoAndar, Loggi, JusBrasil, iFood, Loft, Olist
• Big Tech: Alphabet (Google), Amazon, Apple, Meta, Microsoft
• Other Tech: Netflix, Uber, Lyft, Airbnb, Spotify, Snap, X (Twitter), Pinterest
• Strong Fraud Prevention Start-Ups: Sardine, Signifyd, Riskified, Feedzai, Sift, Forter, Incognia, Unico, Idwall, ClearSale The Selection Process Materials about Nova, including a pitch deck and pitch videos, will be shared during the process.
• Screening Call: 15-min call with HR to align on requirements and qualifications
• Introduction Interview: 30-min call with the Hiring Manager for a quick review of past experience
• Deep Dive Interview: 60-min call with the Hiring Manager to go deep on past experience and profile
• Bar Raiser Interview: 45-min call with another leader to validate the assessment with a second opinion
• Cultural Fit Interview: 30-min call with the CEO to evaluate culture fit and answer questions about Nova The Offer Package
• Model: PJ
• Compensation: [R$ 30,000 – R$ 40,000 / month]
• Stock Options: aggressive stock option grants
• Other

Benefits:
premium health insurance, flexible hours, paid vacation and Wellhub If you're excited about building the rails of the next generation payment network alongside a small team of high-caliber, highly motivated professionals, we'd love to hear from you.