**About Neon** At Neon, every idea matters and can transform the financial lives of thousands of Brazilian women and men who believe the sky is the limit. We seek people who want to make a real impact and grow alongside us! Our pace is intense, just like the learning experience with highly talented individuals and collaborative teams that deliver real impact from day one—plus the bonus of working from anywhere in Brazil. Here, innovation and technology go hand in hand, and diversity is a strategic business decision and a commitment that shapes our decisions and ensures an inclusive environment for everyone. We value collaboration, open dialogue, and solutions that truly understand the needs of the people using our products. If you are someone who enjoys building, testing, learning, and committing to excellence, Neon is the place for you. Join a team that isn’t afraid to dream big and works together daily to raise the bar—making money flow and the world grow. **Come \#LiveInBlue!** **About the Opportunity:** We are looking for a highly objective, practice-oriented, and solution-driven **Staff Data Scientist I**, to lead the end-to-end development and evolution of our cutting-edge credit risk models. If you possess strong technical maturity, prefer agile resolution of complex problems over academic idealism, and take pride in seeing your models run consistently and scalably in production, this role was made for you. ### **Responsibilities and Duties:** * Develop, test, and deploy high-performance tabular models focused strictly on classification and credit risk problems. * Ensure full model lifecycle management (end\-to\-end), from raw data manipulation and extraction through production monitoring and operational support. * Investigate and intervene swiftly and practically in real-world scenarios involving model failure or degradation in production, ensuring resilience of credit operations. * Apply advanced model interpretability techniques to translate complex statistical behaviors into clear inputs for business decision-making. * Serve as an advanced technical reference (Staff), raising the bar for data engineering and modeling across the entire data science team. ### **Requirements and Qualifications:** * **Production Experience:** Proven track record deploying large-scale tabular models in real production environments. * **Boosting Algorithm Expertise:** Deep practical knowledge of developing and calibrating boosting algorithms such as XGBoost and LightGBM. * **Interpretability Tools:** Advanced technical proficiency in explainability frameworks, specifically SHAP. * **SQL Mastery:** Ability to perform complex data manipulations directly, swiftly, and effectively (writing clean queries, complex aggregations, and optimization). * Intermediate English. **If you join Neon, it’s important that you:*** Adapt easily to diverse scenarios and challenges in a dynamic environment * Focus on results, with the ability to prioritize high-impact initiatives * Work autonomously and collaboratively in a fully remote setup **And what will you find here?*** A truly remote work model, with team gatherings every three months in São Paulo. Also includes a home office kit allowance and coworking space partnerships; * iFood Benefits Card—you customize your package with meal, food, and mobility benefits; * Gympass, offering access to gyms and online classes; * Parental support including childcare or babysitter allowance and extended parental leave; * Medical and dental insurance; * Open English: lesson packages with exclusive discounts for Neowners and dependents; * Discounts on MBAs and specializations at USP ESALQ. **LGPD at Neon** Neon adopts a policy to ensure control and transparency in the processing of personal data of all individuals—including those interested in joining our team. Candidate information collected during Neon’s open recruitment processes is handled strictly in accordance with the LGPD. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
João Silva
Indeed · HR
João Silva
Indeed · HR
