Data Scientist Pleno (Crédito)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist Pleno (Crédito) based in Brazil.

This role sits within a Data & AI environment focused on building and evolving predictive intelligence for credit products. You will work with large-scale transactional data to develop machine learning solutions that create measurable business impact. The position combines statistical expertise, credit risk knowledge, data engineering, and hands-on model production. You will own Data Science projects from problem definition through deployment, monitoring, and continuous improvement. Close collaboration with Credit, Product, Operations, and other business teams will be essential to translating analytical insights into effective credit strategies. You will also have the opportunity to explore AI agents, MLOps practices, and modern development tools in a highly collaborative and autonomous environment.

• Credit Data Science: Develop and evolve predictive credit intelligence, applying machine learning and statistical techniques to solve complex business problems and improve the efficiency of credit operations.
• End-to-End Project Ownership: Lead Data Science initiatives with autonomy, from defining and scoping problems together with Product and Operations teams through solution development, production deployment, impact measurement, and continuous iteration.
• Model Lifecycle Management: Manage the complete lifecycle of machine learning models, including experimentation, validation, publication, monitoring, and ongoing improvement, with appropriate performance metrics and monitoring routines.
• Model Monitoring: Establish and maintain processes to identify and respond to data drift and concept drift, ensuring models remain reliable and effective in production environments.
• Credit Risk Analytics: Conduct analytical studies, identify patterns, and generate actionable insights that support credit efficiency, decision-making, and product evolution.
• Cross-Functional Collaboration: Partner closely with Credit teams across Policy, Analysis, Monitoring, and Collections, as well as Credit Product teams, to translate business challenges into data-driven solutions.
• AI Agents: Develop and maintain artificial intelligence agents that help Product and Business teams explore and analyze data related to credit products and automate relevant analytical activities.
• Production & Scalability: Ensure machine learning solutions are designed and maintained to operate reliably at scale across high-volume transactional environments.
• Innovation & Best Practices: Stay current with Data Science best practices and AI-assisted development tools, evaluating and implementing improvements that increase productivity, solution quality, and delivery effectiveness.

Requirements

• Machine Learning & Statistics: Practical experience with statistical inference and applying machine learning models to solve real-world business problems.
• Big Data & Programming: Strong proficiency in Python, SQL, and Spark for processing, manipulating, and analyzing large datasets.
• Model Production: Hands-on experience deploying machine learning models into production through both live and batch architectures and maintaining them throughout their operational lifecycle.
• Credit Risk: Familiarity with predictive credit risk models, including application, behavioral, or collection models, as well as credit metrics and KPIs, particularly within credit card environments.
• Business Acumen: Ability to communicate technical and statistical results clearly and translate analytical metrics into practical business impact and credit strategies.
• Software Engineering Practices: Familiarity with structured development practices, code quality, and version control using Git.
• Analytical Skills: Strong problem-solving, analytical, and critical-thinking abilities, with a structured approach to investigating data and business challenges.
• Collaboration: Ability to work effectively with Product, Operations, Credit, and other cross-functional stakeholders in a collaborative environment.
• Ownership: Comfortable working with autonomy, taking responsibility for end-to-end deliverables, and continuously improving solutions based on measurable outcomes.
• Education: Bachelor’s degree or equivalent practical experience in Computer Science, Engineering, Statistics, Mathematics, Physics, or a related field.

Benefits

• Work Model: Fully remote / home office.
• Employment: Full-time CLT employment, with an 8-hour workday from Monday to Friday.
• Healthcare: Medical and dental assistance without coparticipation.
• Insurance & Wellbeing: Life insurance, medication assistance, physical activity support, and access to resources supporting physical, mental, and financial wellbeing.
• Mental Health Support: Four free monthly therapy or nutritionist sessions through the available wellbeing program.
• Flexible Food Benefit: Flexible food allowance provided through a Visa card.
• Family Support: Childcare assistance, parental support programs, and extended maternity and paternity leave.
• Education: Education assistance covering 70% of eligible undergraduate and language tuition, as well as support for courses and books.
• Learning & Development: Access to an internal training platform and a continuous learning environment focused on professional development.
• Remote Work Support: Home office allowance, work equipment, furniture assistance, and access to coworking spaces across Brazil.
• Additional Perks: Birthday day off, Happy Hour allowance, employee referral bonuses, annual performance-based bonuses, and a Stock Options plan.
• Work Culture: A collaborative, innovative, autonomous, and flexible environment with a strong focus on employee development and wellbeing.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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