Data Scientist

Description

Working at Azos means having real autonomy and great people by your side. Here, everyone has the space to make things happen and see the results of their own work positively impact thousands of Brazilian families. We believe in a light-hearted, diverse, and collaborative environment where constant exchange fuels collective growth. We have offices in São Paulo and Belo Horizonte, but our team is spread across every corner of Brazil — and it’s precisely this blend of stories and perspectives that strengthens everything we build together. We are Brazil’s largest insurtech, and our values guide every step of our journey: * **Always the best for our customers:** We place customers and partners at the center of everything, striving to deliver the best possible experience. * **We’re only as good as our people:** We value a trusting environment where everyone rows together and has room to grow. * **Inherently nonconformist:** We don’t settle for the basics. We question, test, and create the new. * **Ready and willing:** We face challenges with attitude, resilience, discipline, and lightness — never becoming complacent. **If you seek purpose, freedom to innovate, and a team that plays as one, this could be your place.** ### **About the Role** The Azos Data Science team is responsible for building, evolving, and maintaining data products based on machine learning, aiming to improve the company’s economics: increasing revenue, optimizing costs, boosting customer and partner engagement, and enabling predictability for future events. We’re looking for a **Data Scientist** to build predictive models and data solutions that directly impact the business — from automated decision engines to partner segmentation models, intelligent collections workflows, and engagement initiatives. You’ll work autonomously on problems spanning raw data to production models, while also contributing to computer vision initiatives at the core of our next-generation products. If you enjoy solving complex problems, have experience applying modeling to risk or decision-making contexts, and want to grow within a function where data science sits at the heart of the business, this role is for you. #### **As a Data Scientist, you’ll be responsible for:** * Building and validating supervised and unsupervised models applied to diverse business problems: risk classification, partner segmentation, pattern detection, and engagement modeling; * Developing automated decision engines, translating business rules and model outputs into approval, rejection, and risk parametrization workflows; * Contributing to the development of computer vision models for image analysis and classification; * Collaborating with engineering teams to integrate models and solutions into internal subscription and automation products; * Clearly communicating model results and recommendations to product and business teams. #### **What we expect you to know/have:** * Experience building and validating supervised (classification, regression) and unsupervised (clustering, anomaly detection) models, with emphasis on real-world business problems; * Hands-on experience with automated decision engines applied to risk, credit, underwriting, or similar domains; * Solid foundations in computer vision: image preprocessing, segmentation, and visual classification (OpenCV or similar); * Strong Python skills for modeling and pipeline development (pandas, scikit-learn, Hugging Face); * Ability to conduct exploratory analyses and clearly communicate findings to business stakeholders; * Proficiency with Git and familiarity with cloud environments (GCP or AWS); * Degree in Computer Science, Engineering, or related field. #### **Nice-to-have:** * Practical experience with OCR (Tesseract, PaddleOCR, Google Document AI, or AWS Textract); * Experience with multimodal (vision-language) models such as LayoutLMv3, Donut, or similar; * Experience with deep learning for images (CNNs, object detection, semantic segmentation); * Familiarity with pipeline frameworks like Kedro or similar; * Experience in insurtech, fintech, or contexts involving regulatory or document-based data. **Benefits included in your Azos journey** **Health & Well-being** * Nationwide health insurance (private room), with optional dependent coverage — fully supported by Pipo. * Dental insurance. * TotalPass and Wellhub — to balance body and mind. * Life insurance, bringing greater peace of mind to you and your family. **Family first** * Extended maternity leave. * Extended paternity leave. * Childcare allowance for employees with children. **Development & Career** * Educazos: support for the professional development of our Azonautas. * Stock options as recognition — granted based on eligibility. **Everyday practicality** * iFood Benefits: meal and food vouchers, plus iFood Club membership. * Setup allowance to help equip your workspace. * Pharmacy discounts.