John Deere Data Scientist - Risk Analytics in Johnston, Iowa
There are 7 billion people on this planet. And by 2050, there will be 2 billion more... many moving into urban centers at an unprecedented rate. Making sure there is enough food, fiber and infrastructure for our rapidly growing world is what we’re all about at John Deere. And it’s why we’re investing in our people and our technology like never before in our 175-year history. Here the world’s brightest minds are tackling the world’s biggest challenges. If you believe one person can make the world a better place, we’ll put you to work. RIGHT NOW.
Primary Location: United States (US) - Iowa (US-IA) - Johnston
Function: Data Science & Analytics
Title: Data Scientist - Risk Analytics - 66265
As a Data Scientist at John Deere Financial in Johnston, IA, you will use R, SAS and SQL to investigate, join, and analyze large data sets in order to derive actionable insights for the business associated with credit decisions, portfolio performance, marketing, and other credit operational business partners. The Risk Analytics team has four primary responsibilities: independent portfolio review, credit quality scorecard development, decision automation management, and analytical business insights. This position is responsible for supporting cross portfolio activities driving increases in automation in the credit decision and adjudication process. This role is necessary to sufficiently support the US and CA credit teams and to meet decision automation goals. In addition, you will;
Build and deploy analytical solutions to increase automation in the credit decision and adjudication processes
Develop predictive models using various statistical methods or machine learning algorithms. Model types may include probability of default models, customer behavior modes, loss given default models, etc.
Maintain, monitor, and evaluate the ongoing performance of statistical models and other risk assessment tools in order to remain in compliance with internal and third-party standards and regulations
Visa sponsorship is NOT available for this position
Proven Technical Skills and Experiences
Experience using at least one analytics programming language such as SAS, SQL, R, or Python
An ability to convey information to others through data visualizations
An understanding of basic predictive modeling techniques such as binary logistic regression or continuous regression
Hands-on experience utilizing large data sets from various sources and databases
Interpersonal, Leadership and Teaming Competencies
Experience using machine learning algorithms to build supervised learning models used in predictive analytics
Understanding of JDF (or other lending) business functions, processes, and procedures
Experience analyzing and visualizing data through advanced visualization tools such as Tableau
Education (or equivalent work experience)
- Bachelor's degree in Data Science/Analytics, Actuarial Science, Statistics, Economics, Finance, Engineering or other quantitative discipline
What You'll Get
At John Deere, you are empowered to create a career that will take you to where you want to go. Here, you'll enjoy the freedom to explore new projects, the support to think outside the box and the advanced tools and technology that foster innovation and achievement. We offer comprehensive relocation and reward packages to help you get started on your new career path. Click here to find out more about our Total Rewards Package.
The information contained herein is not intended to be an exhaustive list of all responsibilities and qualifications required of individuals performing the job. The qualifications detailed in this job description are not considered the minimum requirements necessary to perform the job, but rather as guidelines.
John Deere is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, religion, color, national origin, sex, age, sexual orientation, gender identity or expression, status as a protected veteran, or status as a qualified individual with disability.