This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Credit Data Science Specialist based in Brazil.
This is a remote opportunity for a hands-on data professional joining a Credit and Collections function focused on turning complex financial data into actionable business insights.
You’ll combine credit expertise, statistical modeling, and machine learning to improve risk, collections, and portfolio strategies.
The role involves building and monitoring predictive models, developing credit policies, and identifying opportunities for automation.
You’ll work closely with data engineering and cross-functional teams to transform raw transactional data into high-quality features and decision frameworks.
Your analysis will directly influence credit limits, pricing, retention, collection efficiency, and financial performance.
You’ll also develop dashboards and indicators that provide visibility into the health of credit and collections operations.
The environment values curiosity, business understanding, analytical rigor, and the ability to translate data into strategic advantage.
Accountabilities:
- Develop, implement, and monitor credit scoring and churn predictive models using transactional and financial data.
- Analyze revenue trends using statistical techniques such as linear regression and confidence intervals.
- Apply generative AI and advanced analytical approaches to automate and scale credit analysis while maintaining eligibility and validation requirements.
- Conduct portfolio analysis and backtesting, including Vintages and Roll Rates, to inform credit limits, pricing, and retention strategies.
- Build propensity-to-pay models to improve debt recovery and support segmentation of external collection strategies.
- Evaluate the financial feasibility of judicial versus extrajudicial collection approaches.
- Design and maintain real-time dashboards and operational reporting covering KPIs such as First Payment Default (FPD), Provision for Doubtful Accounts (PDD), and debt renegotiation effectiveness.
- Partner with data engineers to develop a useful data lake and transform raw data into structured variable books and high-value features.
- Work with large-scale transactional datasets and internal or external validation databases to generate reliable business insights.
- Collaborate with cross-functional teams to translate analytical findings into credit and collections policies, processes, and strategic decisions.
- Continuously explore ways to improve data analysis, KPI generation, modeling workflows, and operational efficiency through new technologies and AI tools.
Requirements:
- Bachelor’s degree in Statistics, Engineering, Economics, Mathematics, Computer Science, or a related quantitative discipline.
- Hands-on experience using Python to develop and apply statistical and machine learning models, particularly regression and classification algorithms for financial forecasting.
- Solid understanding of the credit lifecycle and experience working with credit and collections indicators such as FPD, PDD, Vintages, Roll Rates, SCR, and Serasa data.
- Proven experience developing predictive models and performing complex statistical calculations.
- Experience creating propensity-to-pay models and analyzing collection and recovery strategies.
- Advanced SQL skills, with the ability to extract, transform, and analyze large-scale transactional datasets.
- Strong understanding of statistical modeling, data analysis, and machine learning concepts.
- Ability to translate raw data into meaningful variables, features, insights, and business recommendations.
- Strong analytical thinking and curiosity, with an interest in understanding how the business operates beyond purely technical requirements.
- Experience with data visualization, dashboards, and KPI development for operational and management reporting.
- Familiarity with AI tools and a willingness to adopt new technologies to improve analytical efficiency.
- Strong communication and collaboration skills, particularly when working with data engineering and business stakeholders.
- Business English is a strong advantage for collaborating with international teams and contributing to global initiatives.
Benefits:
- Remote work: Work from anywhere within Brazil.
- Wellness membership: Complimentary Gold+ access to fitness, wellness, meditation, nutrition, and mental wellbeing resources, with the option to add up to three family members.
- Emotional wellbeing: Access to a dedicated wellbeing program with personalized journeys, including up to 52 individual therapy sessions per year and on-demand resources.
- Healthcare: Health, dental, and life insurance.
- Flexible benefits: A flexible benefits program that allows you to customize selected benefits according to your needs.
- Flexible schedule: Collaboratively define working schedules with your leadership team based on time zones, team requirements, and personal routines.
- Paid time off: Vacation eligibility after six months, plus additional annual days off, tenure-based extra days, and an additional day off for your birthday.
- Parental leave: 100% paid parental leave for new parents, with extended leave and a gradual return-to-work option for parents giving birth.
- Career development: Access to learning platforms, interactive development sessions, personalized growth plans, and internal career opportunities.
- Inclusive culture: A collaborative environment focused on wellbeing, diversity, belonging, continuous learning, and equitable opportunities.
- Employment type: The position is offered exclusively as a CLT employment arrangement in Brazil.
How Jobgether works:
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!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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