Senior Data Scientist Leader

Description

Job Summary: Senior Data Scientist Leader for credit risk models (PJ), connecting business, strategy, regulation, data, and technology to evolve models and generate value. Key Highlights: 1. Lead the credit risk modeling agenda for SMEs. 2. Promote methodological advancement and high technical standards in modeling. 3. Develop and strengthen the technical team, driving performance. Senior Data Scientist Leader Country: Brazil By joining the Santander **Risk Models \& Analytics PJ** team, you will work in an area responsible for models and ratings for the organization’s Corporate (PJ) segment, playing a central role in advancing the analytical credit risk agenda—specifically for SMEs. We seek a professional with a solid technical foundation and strong leadership capability, able to connect business, strategy, regulation, data, and technology to guide the evolution of models, processes, and people—ensuring value generation in segment results. **Your responsibilities here will include:** * Leading the **SME Credit Risk Models** agenda *(application score, behavior score, rating, among others)*, ensuring clear direction, technical advancement, and alignment with the company’s strategic priorities. * Defining priorities and guiding the evolution of models, ratings, indicators, and analytical initiatives within the area—connecting business needs, risks, and regulatory requirements. * Collaborating closely with stakeholders across Risk, Policy, Business, Data, Technology, and global teams to promote alignment, clarity of direction, and sustainable execution of initiatives. * Ensuring the evolution and maintenance of the area’s model portfolio, with oversight of performance, monitoring, stability, governance, and improvement opportunities. * Promoting methodological advancement and high technical standards in deliverables, encouraging robust analytical approaches, applied innovation, and sound modeling practices. * Leading the evolution of the area’s ways of working, driving opportunities for automation of critical processes and applied use of artificial intelligence as levers of efficiency, scalability, and productivity. * Ensuring effective prioritization and capacity allocation for the team—balancing strategic agenda, regulatory demands, methodological advancement, and business needs—while providing clear *roadmap* visibility to senior leadership. * Developing and strengthening the technical team, fostering growth, cultivating internal subject-matter experts, and building a high-performance environment. * Representing the area in key forums and executive interactions, demonstrating synthesis ability, directional clarity, and influence. **Education and Languages** * Bachelor’s degree in Statistics, Computer Science, Physics, Applied Mathematics, Engineering, or related fields. Degrees in quantitative disciplines are preferred. * Postgraduate studies or specialization in Data Science, Credit Risk, Analytics, Management, or related areas. * Master’s and/or PhD degrees are advantageous. English or Spanish is essential for interactions with global teams. * **Hard Skills** * Strong experience in applied statistics, predictive modeling, and machine learning. * Relevant experience in credit risk modeling for individuals (PF) or corporates (PJ). * Ability to bridge technical vision, business needs, governance, and implementation feasibility. * Experience in complex analytical environments with strong business–technical interface. * Experience leading analytical agendas, prioritizing initiatives, and engaging multiple stakeholders. * Knowledge and experience with programming languages and large-scale data manipulation. Experience leading Data Science, Modeling, or Analytics teams. * **Soft Skills** * Strong leadership, influence, and cross-functional alignment capabilities. * Strategic vision and ability to translate technical topics into business agendas and organizational impact. * Clear communication and ability to translate technical topics into actionable directions and recommendations for stakeholders. * Decision-making ability that balances technical rigor, pragmatism, and practical feasibility. * Ability to develop people, raise the team’s technical bar, and foster a high-performance environment. * Acting as a partner and enabler for the team in managing day-to-day operations and transformative agendas.