Data Scientist Specialist - Tech Lead - AgriBusiness (Risk Analytics)

Description

**Company Description** Serasa Experian is Brazil's first and largest Datatech company. A leader in intelligence solutions for risk and opportunity analysis, focused on credit, authentication, and fraud prevention journeys. With cutting-edge technology, innovation, and top talent, it transforms risk uncertainty into the best decision—helping individuals achieve their dreams and businesses of all sizes and sectors thrive. We have 22,000 people operating across 32 countries, and every day we invest in new technologies, talented professionals, and innovation to help all our customers maximize every opportunity. With corporate headquarters in Dublin, Ireland, Experian is listed on the London Stock Exchange (EXPN) and is a constituent of the FTSE 100\. **Job Description** We are seeking a Data Scientist Specialist to join our Agribusiness Risk Management team. The professional will work within a highly skilled team of data scientists, developing models, features, and analytical solutions that support strategic decisions and innovation in agribusiness. This professional will also play a key role in defining the analytical architecture, technical standards, and direction of data science solutions—serving as the technical reference for the team and as the bridge between business, engineering, and product. **Responsibilities:** * Develop risk models that optimize credit analysis and underwriting capacity in Agribusiness. * Define technical approaches, technology stacks, and development standards for models and analytical pipelines. * Document and communicate model results clearly and actionably to diverse stakeholders. * Deliver presentations and gather feedback from internal and external customers. * Collaborate with multidisciplinary teams—including Engineering and Product—to understand needs, identify opportunities for process and product improvements from a modeling perspective. * Explore new variables and information sources to enhance model predictive power. * Evaluate and implement new techniques/technologies to improve risk model efficiency and accuracy. * Continuously monitor alignment between data science technical decisions and business objectives. * Serve as a technical reference (tech lead) for data scientists and analysts—supporting methodological decisions and code/model reviews. * Lead the evolution of risk model architecture (features, validation, monitoring, MLOps). * Evaluate trade-offs among model complexity, performance, interpretability, and governance. * Support technical planning for medium- and long-term analytical initiatives. **Qualifications** **Basic Requirements:** * Bachelor’s degree in Data Science, Mathematics, Engineering, Statistics, Computer Science, or related fields. * Proficiency in Python and experience with libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, Jupyter, etc. * Strong command of Machine Learning techniques applied to real-world risk/credit problems—including model validation, bias control, temporal stability, and explainability. * Practical experience designing complex features and evaluating variable impact in production. * Ability to review, refactor, and guide analytical code toward quality, efficiency, and reproducibility standards. * Experience in risk modeling. * Experience participating in analytical or technical architecture decisions (data, models, pipelines). * Proficiency in querying and manipulating databases for model construction and validation. * Familiarity with version control tools such as Git and Bitbucket for managing and collaborating on code projects. * Communication skills to present technical results clearly and persuasively. * Ability to work independently and collaboratively, with excellent communication and interpersonal skills. **Desirable/Preferred:** * Academic or professional experience in Agribusiness. * Experience serving as a technical leader or subject-matter expert in data teams. * Ability to guide junior professionals and influence technical decisions without formal authority. * Experience in software engineering and Machine Learning engineering. * Ability to assess the use of LLMs and AI agents as part of the analytical strategy. * Experience working in agile and collaborative environments, with a focus on continuous value delivery. * Knowledge of other programming languages, such as R, SQL, Scala, and Java. **Additional Information** Serasa Experian is much more than you imagine. With a purpose to create a better future by expanding opportunities for individuals and businesses, in Brazil we are over 4,000 people working across diverse teams and specialties. Here, every skill and form of diversity complements one another—you can work on what you love most. We are committed to building an inclusive culture and an environment where people can balance their careers with personal commitments and interests—prioritizing well-being. We are deeply dedicated to being one of the country’s best and most innovative employers—enabling extraordinary experiences and careers for our people. Our strong people-first approach is externally recognized through numerous market certifications: we have been awarded Great Place To Work™ in 24 countries and hold the international Top Employers certification; we are also recognized as one of the best employers for young professionals and maintain a 4.6 rating on Glassdoor. Each recognition confirms we’re on the right path—providing an ever-better workplace for our talents. Experian Careers \- Creating a better tomorrow together Find out what it's like to work for Experian by clicking here