Staff AI Data Scientist

Build the future of payments with AI, Pix & Open Finance

Type: Full-Time

Language: English

Location: São Paulo, Brazil (Hybrid)

Reports to: CPO

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 functions as an infrastructure bridge between traditional credit cards and Pix, allowing consumers to 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 had top-tier venture capital investors (Monashees, Canary, Canaan and Propel) since its inception

They recently raised a large Series A and are 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 data scientist to build and improve the foundational models that are pivotal to product suite's value - with fraud prevention being the initial core focus. Key responsibilities:

• Designing, building and deploying ML models for real-time fraud and risk decisioning - starting with transaction-level fraud prevention and chargeback prediction at the moment of authorization
• Owning the full model lifecycle: feature engineering, training, validation, deployment, monitoring, and continuous retraining as fraud patterns evolve
• Building the data foundations that power our models - defining schemas, pipelines, and feature stores in close partnership with engineering
• Balancing fraud losses against approval rates and user friction, treating risk decisioning as a product lever, not just a defensive function
• Expanding beyond fraud into the models that power the broader product suite: credit and limit decisioning, installment risk, personalization, and merchant intelligence
• Leveraging Brazil-specific data rails (Pix, Open Finance) and AI tooling to build defensible advantages incumbents can't easily replicate
• Shaping our data culture: rigorous experimentation, hypothesis-driven analysis, and AI leveraged in every facet of the org

This is your chance to be a protagonist at work, working on challenging projects with a meaningful impact, as part of a select team in a uniquely ambitious new payment network company.

The Qualifications

Required

• 7+ years of full-time work experience in data science and/or machine learning roles, with models deployed in production
• Hands-on experience building and shipping ML models for fraud prevention, credit risk, or similar real-time decisioning systems
• Strong proficiency in Python and SQL, and experience with the modern ML stack (model training, deployment, and monitoring in production environments)
• Bachelor's (or equivalent) degree in Engineering, Computer Science, Statistics, Mathematics or related technical fields
• Full professional proficiency in English

Preferred

• Experience with fraud/risk in payments specifically - chargebacks, transaction fraud, account takeover, or AML
• Experience at high-performing fintechs, financial services companies and/or startups
• Advanced degree (MSc/PhD) in a quantitative field
• Graduated from top schools and/or with top grades
• Participated and/or won in competitions (e.g., Kaggle), received work-related awards; Or other demonstrable proofs of ambition, intelligence and resilience

The Target Companies

Candidates with at least 2 years of full-time experience in the companies below will be prioritized:

• Strong Local Fintechs: 
• Acquirers: Cloudwalk, Stone, 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

The Selective Process

Materials about Nova, including a pitch deck and pitch videos will be made available through the process

• Screening Call: 15min call with HR for alignment on requirements and qualifications
• Introduction Interview: 30min call with Hiring Manager for a quick review of past experiences
• Deep Dive Interview: 60min call with Hiring Manager to deep dive on past experiences and profile
• Bar Raiser Interview: 45min call with another Leader to validate assessment with a 2nd opinion
• Cultural Fit Interview: 30min call with CEO to evaluate culture fit and answer questions about Nova

The Offer Package

• Model: PJ
• Compensation: R$20-30 K
• Stock Option: aggressive stock option grants
• Other Benefits: premium health insurance, flexible hours, paid vacations 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.