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 customer management team. You will use data science and analytics to better understand data patterns, identify opportunities, predict next best action, and optimize account management, among others. You will be based in Indaiatuba/SP and align with the JDF Loss Forecasting and Customer Management team headquartered in Johnston-Iowa-USA, aiming to execute and deliver the analytics and insights needed to support the business units. Join a team that is passionate about making a difference by applying different techniques to solve problems and leverage data as an asset.

OBS: Please submit your resume in English!

Main Responsibilities

• 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 behavior 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.

What Skills You Need

• Bachelor’s degree in quantitative field (e.g statistics, data science, mathematics, economics, computer science);
• Advanced English level is mandatory (written and verbal skills);
• Proficiency in at least one of the following data science software tools (SAS, Python, PySpark, R, SQL);
• Analytical approach will include but is not limited to logistic regression, survival analysis, transition matrix, time series, neural networks, machine learning, among others;
• Microsoft office skills are required (e.g. Excel, Powerpoint, Word, Outlook);
• Flexibility in schedule to work with colleagues and international customers across the multiple countries.

What Makes You Stand Out

• Master’s degree in quantitative field;
• Experience performing statistical analysis of moderate to highly complex structured and unstructured data from multiple sources that may not have common identifiers;
• Previous hands-on experience building predictive models through statistical modeling techniques.