Data Scientist - Indaiatuba/SP

As a Data Scientist for John Deere Financial, you will be responsible for developing, delivering and validating predictive analytics models to increase and accelerate Data Science & Analytics capabilities working in support of JDF’S international credit portfolios (Europe, Asia and Latin America). You will use data science and analytics to better understand data patterns, identify opportunities, predict probability of default related to the credit risk, among others. You will be part of a global analytics organization, working from our Global Capability Center in Indaiatuba, Brazil, while partnering with the John Deere Financial International Risk Analytics team in Johnston, Iowa, USA. This is a unique opportunity to apply cutting-edge analytics, machine learning, and data science techniques to real-world business challenges, gaining exposure to international markets while helping shape the future of credit risk decisioning and portfolio management. Join a team that is passionate about making a difference by applying different techniques to solve problems and leverage data as an asset. 

 Ps: English is required for all communications and documents 

• Participate in business partner meetings, brainstorming sessions, and workshops to capture business objectives and prioritize opportunities; 
• Identify best analytical techniques that can be effectively applied to achieve business objectives and interpret the next best action through data driven insights; 
• Build, test and deploy credit scoring and other types statistically-based predictive models; 
• Maintain and enhance the existing models through various statistical tests; 
• Develop, implement and analyze reports to keep business partners and management informed of key risk and performance information; 
• Investigate potential areas of concern and communicate results of analysis to senior management; 
• Work in a highly interactive, team-oriented environment with data scientists, data analytics catalysts, analytics data engineers and business intelligence analysts distributed across multiple countries.

• Bachelor’s degree in quantitative field (e.g statistics, engineer, data science, mathematics, economics, computer science among others);
• Advanced English level is mandatory (written and verbal skills); 
• Previous hands-on experience building predictive models through statistical modeling techniques. Analytical approach will include but is not limited to logistic regression, survival analysis, transition matrix, time series, neural networks, machine learning, among others; 
• Proficiency in at least one of the following data science software tools (SAS, Python, PySpark, R, SQL); 
• Microsoft office skills are required (e.g. Excel, Powerpoint, Word, Outlook);
• Demonstrated ability to communicate complex analytical insights in a manner which is clearly understandable by non-experts;Commitment to team success and a proactive, collaborative approach to problem solving and different cultures and time zones.

• Master’s degree in quantitative field;Previous experience with credit risk parameters (e.g. PD, LGD, and EAD) that support the expected credit loss estimation;
• Experience applying Generative AI, Large Language Models (LLMs), or AI-assisted analytics solutions to improve business processes, decision-making, or productivity;
• Familiarity with cloud-based analytics platforms and modern data science environments (e.g., Databricks, AWS, Azure, or similar);
• Experience performing statistical analysis of moderate to highly complex structured and unstructured data from multiple sources that may not have common identifiers.