John Deere Data Scientist in Johnston, Iowa
At John Deere, we run so life can leap forward. This powerful purpose is our promise to humankind that we will dream, design and deliver breakthrough products that sustain our world for generations to come. The world is counting on us to feed billions of people and build vital infrastructures in villages, towns, and megacities. We live up to the legacy our founder forged in a one-room blacksmith's shop nearly two centuries ago by creating a culture that brings out the best in all of us. A culture where great ideas thrive because every voice is heard.
Primary Location: United States (US)- Iowa- Johnston
Function: Data & Analytics (CA)
Title: Data Scientist- 86001
Onsite/Remote:Partial Remote Position
Visa sponsorship is NOT available for this position
As aData Scientistfor the Risk Analytics Team at John Deere Financial (JDF), you will
Participate in the development and deployment of predictive models for purposes such as credit risk scoring, loss given default, and other behavioral models
Analyze and interpret historical data covering the entire credit lifecycle and recommend actions for optimizing and automating business decisions.
Collaborate with a variety of technical and non-technical stakeholders to understand business needs and deliver a wide range of impactful analytics products
What Skills You Need
3+ years of work experience in data science or a related field
High proficiency in at least one of the following: R, SAS, Python
Demonstrated proficiency within a standard data science development process, including all phases of data preparation and exploration, along with model training, evaluation, and deployment
Experience using at least one data visualization tool or technique (such as Tableau, Power BI, R Shiny, Plotly) for articulating data insights to diverse groups of business partners
Effective communication skills and an ability to solve problems and deliver solutions as part of a collaborative cross-functional team
What Makes You Stand Out
Experience connecting to and utilizing a wide variety of on-prem and cloud-based data sources and technologies (e.g. relational databases, data lake environments, etc.)
Proficiencies in multiple data science programming languages such as R, SAS, Python, SQL
Practical experience with supervised and unsupervised learning algorithms, including binary classification, regression, clustering, and/or other ML techniques.
An understanding of model validation and model monitoring best practices
Familiarity with version control systems such as Github
Knowledge of finance and accounting concepts and financial products
Ideally you will have a degree or equivalent related work experience in the following:
Bachelors degree in quantitative field (e.g. mathematics, statistics, data science, analytics, computer science, information technology, economics, engineering).
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 (http://www.deere.com/en/our-company/john-deere-careers/why-john-deere/) 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.
An Equal Opportunity Employer, John Deere requires a diversity of people, perspectives and ideas to address the complex challenges of its global business. 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, status as a protected veteran, or status as a qualified individual with disability.