CNH Industrial

Data Scientist

Location US
ID
2021-17119
Category
Business Operations
Position Type
Full-time

Overview

CNH Industrial is a global leader in industrial goods. We provide farmers with cutting-edge technologies to help them feed a growing world population and we assist in building and rebuilding cities and infrastructures, all with future-proof powertrain solutions. With our Case IH, New Holland Agriculture, Case and New Holland Construction, and FPT Industrial brands, and comprehensive solutions for financing and aftermarket services, we’re driven to meet the needs of our customers.

 

The Data Scientist is responsible for developing predictive models, insights and innovative solutions for our agricultural equipment customers. You will apply modern machine learning methodologies to large geospatial, satellite imagery and machine generated datasets to maximize the productivity and ease of use of the equipment manufactured by CNH Industrial. As a Data Scientist you will work closely with product managers, engineers and subject matter experts to deliver customer insights onboard the vehicle and in the cloud. You will proactively apply cutting edge technology for the advancement of precision agriculture and large agricultural equipment automation.

Responsibilities

  • Solve complex optimization problems using statistical, algorithmic, data mining and visualization techniques
  • Design and implement the required technical architecture to support machine learning, geospatial data analytics and equipment automation
  • Work with product management and other stakeholders to test hypothesis and validate statistical correlations to be used in a production software environment
  • Create new and innovative solutions by applying a variety or predictive modeling, machine learning/deep learning techniques
  • Communicate effectively with all stakeholders
  • Other related duties as required

Qualifications

Required Qualifications:

  • Bachelor's Degree in Data Science, Applied Mathematics, Computer Science or otherwise research-based field
  • 3 or more years of experience working on advanced analytics projects, being able to demonstrate the development of machine learning algorithms and predictive models
  • Understanding of supervised and unsupervised learning techniques including variable selection, feature engineering, model generation, model diagnostics and deployment
  • This is a remote opportunity candidate can reside anywhere in the US 

Preferred Qualifications:

  • Agricultural, construction, automotive or similar background
  • Experience with customer facing web and mobile applications
  • Experience with geospatial data, visualization tools and precision farming software
  • Proficient with Python, R, Matlab, Azure DB
  • ASP.NET, C#, T-SQL, HTML5, Ajax/JavaScript, CSS
  • Experience with Microsoft data science tool stack on Azure
  • Functional knowledge of version control tools such as Git
  • Proven experience working in a fast-paced team environment

EEO

CNH Industrial is an equal opportunity employer. This company considers candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Applicants can learn more about their rights by viewing the federal "EEO is the Law" poster and its supplement here

 

CNH Industrial participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. You can view additional information here.

 

If you need reasonable accommodation with the application process, please call 1-800-889-4422 option 1 and then option 5, or contact us at narecruitingmailbox@cnhind.com.

 

Read about our company’s commitment to pay transparency by clicking this link: pay transparency notice.

 

Options

Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
Share on your newsfeed

Need help finding the right job?

We can recommend jobs specifically for you! Click here to get started.