Job Summary: Bradesco is seeking a Senior Data Scientist to optimize credit policies, reduce delinquency, and provide technical leadership in data science and automation. Key Highlights: 1. Optimize credit policies and reduce delinquency 2. Technical leadership in data science and automation 3. Build machine learning and MLOps pipelines **About Bradesco** Bradesco is one of Brazil’s largest financial groups, with a history marked by pioneering spirit and innovation. Through our broadly diversified portfolio of financial products, banking services, and insurance offerings, we contribute to individuals’ aspirations and to the sustainable growth of businesses and society. Join our financial ecosystem and impact the experience of millions of people! At Bradesco, we value diversity in all its forms. Therefore, our job openings are open to all individuals, regardless of gender, race, sexual orientation, disability, age, or any other characteristic. Learn more at https://banco.bradesco/html/classic/sobre/index.shtm **Responsibilities and Duties** What is our Credit Team? Our mission is to ensure efficient management of credit granting and maintenance, guaranteeing profitability and solid growth of the Organization’s assets. Work model: Hybrid – 2 days onsite Unit: Osasco/SP **Your Day-to-Day** As a Senior Data Scientist, you will work within the Credit and Credit Recovery Management area, and your main responsibilities will include: * Develop and implement advanced analytical solutions to optimize credit policies and reduce delinquency, ensuring scalability and governance of production models; * Build machine learning pipelines and MLOps practices to support strategic decision-making; * Serve as the technical leader, structuring or reorganizing the team to strengthen competencies in data science and automation, promoting collaboration and alignment with departmental objectives; * Conduct competency assessments in data science, engineering, and MLOps; identify gaps; and propose plans for technical development, restructuring, or upskilling as needed; * Establish a periodic ritual to review the analytical backlog, align priorities with stakeholders, manage regulatory complexities, and ensure deliverables bridge technology and business outcomes. **Requirements and Qualifications** What do you need to have or know? * Bachelor’s degree completed in Statistics, Mathematics, Data Science, Engineering, Economics, etc. * Technical knowledge of advanced statistics, predictive modeling, and machine learning techniques, including complex models such as ensembles, gradient boosting, and neural networks; * Experience handling large volumes of data in distributed environments; * Prior experience in related areas such as credit, collections, risk, or analytics, with hands-on experience developing predictive models and automating processes; * Proficiency in Python, SQL, and PySpark; familiarity with MLOps practices using MLflow; and experience deploying pipelines in Big Data environments. It’s a plus if you have: * Certifications in Data Science, Machine Learning, or Cloud platforms (AWS, Azure, or GCP); * Experience in credit granting and recovery; * Intermediate English for technical reading. **What We Offer** At Bradesco, we value health and well-being, offering an extensive portfolio of benefits to all our employees: * Profit Sharing (PLR) or Bonus: Based on position eligibility* * Health Insurance * Dental Insurance * Life Insurance * Food Allowance * Meal Voucher * 13th Food Basket * Total Pass * Transportation Voucher (optional enrollment) * Discounts on products and services from partner companies * Private Pension Plan (optional enrollment, with financial contribution from Bradesco Organization) * Bradesco Well-Being Program: health, well-being, and quality-of-life initiative * Unibrad: Bradesco Corporate University * Fee Waivers: special conditions across various products and services * Daycare or Nanny Assistance * Extended Paternity Leave of 20 days * Maternity Leave of 180 days, with assisted support from pregnancy through postpartum