Lead Data Scientist

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

At Caterpillar, we work to help our customers build a better world. Without our team of talented, bright and driven individuals, we wouldn’t be the Caterpillar we are today. Now, this is your chance to join our team and do the work that matters. We want you to help us enable customer success, make progress possible around the world and help our communities grow and thrive.

As a Lead Data Scientist, you’ll have a unique opportunity to be part of a team that aims to take Caterpillar and dealer warranty operations to a whole new level through operational and platform transformation. You’ll work closely with multiple different teams across Caterpillar (Product Groups, Industry teams, Global Purchasing, Global Quality, Cat Insurance, Global Service, Treasury, Corporate Accounting, Goodwill, and more) to analyze, explore, and interpret complex data.

Job Duties/Responsibilities may include, but are not limited to:  

• Own the data gathering, mining, and interpretation requirements for the warranty transformation program
• Lead workshops to capture as-is data analytics/reports, pain points, and identify innovative ideas that drive operational improvement
• Research new analytical tools/technology for analyzing high volumes of complex data and recommend data model optimization and algorithms to improve data effectiveness and accuracy
• Explore and recommend new technologies/capabilities that enable individual warranty claim text stories to be summarized accurately
• Develop models that can summarize multiple warranty claim stories and present accurate failure data insights to product groups
• Connect sources of data and develop models to identify abnormal findings, such as repairs compared to failure rates
• Develop methodologies that allow data to be self-learning or be kept up-to-date over many years
• Interpret high volumes of complex data, provide simple business insights, and incorporate appropriate data visualization technologies
• Own the development and implementation of prioritized, multi-generational roadmaps for the to-be processes, capabilities, and analytical needs
• Partner to assess the technical feasibility of to-be ideas, development timelines, and investment needs
• Determine risks, dependencies, and assumptions
• Define baseline and to-be value measurement plans that have increased efficiency and simplicity at their core
• Support the learning and adoption phase of the warranty transformation program with Cat and dealer business partners

Skills:

Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions. Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision. Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems. Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services. Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages. Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use. Requirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.

Basic Qualifications:  

Bachelors, Masters, or PhD degree in Statistics, Data Science, Business Analytics, Predictive Analytics, Mathematics, Computer Science, Engineering, Informatics, Information Systems Management, or equivalent technical degree.

Top Candidates will also have:

• Extensive experience (typically 6 years+) with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc.
• Passion for raising the bar and delivering a world class experience
• Proven ability to investigate complex data analysis and recommended solutions with high autonomy
• Strong financial and business acumen to analyze, interpret, and make strategic recommendation regarding business investments and projected value
• Demonstrated involvement in innovation and use of technology to solve problems
• Strong skills in organization, collaboration, attention to detail, influencing, communication, change management, and gaining commitment
• Must be willing to travel up to 10% of working time

Location: Peoria IL 

Visa Sponsorship is not available for this position. This employer is not currently hiring foreign national applicants that require or will require sponsorship tied to a specific employer, such as, H, L, TN, F, J, E, O. As a global company, Caterpillar offers many job opportunities outside of the U.S which can be found through our employment website at www.caterpillar.com/careers. Posting Dates:

April 1, 2024 - April 3, 2024 Any offer of employment is conditioned upon the successful completion of a drug screen.

EEO/AA Employer. All qualified individuals - Including minorities, females, veterans and individuals with disabilities - are encouraged to apply.