Senior Data Scientist

About Credix Credix is a FinTech company dedicated to growing businesses in Latin America.Building on our expertise, we now focus on providing a tailored Buy Now, Pay Later (BNPL) solution for B2B transactions in Brazil with our platform, CrediPay.CrediPay is created to help business grow their sales and improve their cashflow efficiency through seamless and risk-free credit offering.Sellers offer their buyers flexible payment terms at an attractive price point and receive upfront payments.We manage and protect our clients from any credit & fraud risk, letting them focus only on what matters: increased sales and profitability.Why choose Credix?Become part of a forward-thinking start-up where boldness and a commitment to excellence are paramount, and your personal and professional development is at the forefront.Work alongside a dedicated team of bright individuals driven by an Olympian mindset to excel in every aspect of our operations.Together, we aim to build with velocity, utilizing innovative embedded finance strategies to expand business operations in Latin America.Experience a close and supportive work atmosphere where collaboration thrives, wise judgment guides our decisions, and you can learn, grow, and take on meaningful responsibilities.About the job We're looking for a Senior Data Scientist to join our Risk & Collections team.You'll operate with high autonomy, own critical problem areas, and deliver value that moves the needle - from credit performance to capital efficiency.This isn't a research role.You'll work side-by-side with engineering, product, and operations to deploy models, run experiments, and improve the core systems that decide: Who gets funded How and when we collect Where we allocate risk capital You'll report to the Head of Risk and collaborate closely with our data science and engineering team.You'll work across the entire risk lifecycle - from first impression to final repayment - applying data science to maximize portfolio performance and capital efficiency.Your focus: deliver models and systems that make better decisions, earlier.Specifically, you will: Model borrower risk : Build and refine probability-of-default (PD) and loss-given-default (LGD) models to inform underwriting and exposure sizing.Detect and prevent fraud : Develop fraud signals and real-time scoring logic to flag suspicious behaviors - from application spoofing to behavioral anomalies post-purchase.Prioritize recovery actions : Predict repayment propensity and optimize collections targeting - so we know who to contact, how , and when .Design experiments : Run tests across channels, messages, and strategies - not for learning's sake, but to improve recovery, reduce loss, or increase throughput.Deploy your work : Work closely with engineering to embed models and logic into our core credit and collections systems.Create leverage : Equip the Risk, Credit, and Ops teams with tools, insights, and automation that scale smarter decisions.What We're Looking For 5+ years of experience applying data science to business-critical problems.Strong command of SQL , Python , and the practical use of ML techniques (e.g., classification, uplift modeling, time series, or embeddings).Experience deploying models in production - including versioning, validation, and post-deployment monitoring.Comfort working autonomously with a high bar for quality and impact.Experience working with product or engineering teams to embed model logic into live systems.Solid understanding of business economics: marginal value, yield, CAC/LTV, or credit-related KPIs.Nice to have: Background in lending, collections, or credit analytics.Experience with experimentation frameworks or causal inference.Exposure to NLP or classification techniques (e.g., message quality prediction).Languages: Fluent in Portuguese and English (written and verbal).What we offer Collaboration and team spirit thrive best in an in-office environment.Our office provides a vibrant and engaging workspace where team members can connect, innovate, and grow.With access to our offices in Sao Paulo, you'll immerse yourself in a culture of innovation and collaboration.But that's just the beginning - here's what else we offer: A culture of learning and experimentation: where you are encouraged to explore new ideas and technologies Competitive salary package: Your hard work deserves recognition, and we ensure you're well-rewarded for your contributions.Equity stock options plan: Be a part of our journey towards success and share in the rewards.Paid holidays: Enjoy the flexibility to recharge and rejuvenate Off-sites: Awesome team building, unforgettable memories, and adventures ensured during our team off-sites.