Associate Data Scientist

Key Skills

Java Programming, Teamwork, Management, Python Programming, SQL, Big Data Technology, Machine learning techniques, Data science techniques, Data Mining, Data Visualization, R Programming, Statistics, SAS, Statistical modeling, Large scale data processing, Mathematics, Dataiku, Data Analysis

Job Description

The Product Support and Logistics Division (PSLD) is one of the most innovative divisions within Caterpillar. In PSLD, as within all of Caterpillar, our priority is our customers and helping them build a better world. We touch nearly every element of the services value stream from procurement to design and manufacturing to distribution. PSLD is responsible for Aftermarket Parts Distribution?of?Cat Parts, Integrated Logistics, segment Procurement?and the?design and?manufacture?of Wear Components (Undercarriage and GET) and Maintenance Components (Seals, Tubes & Hardware, Hose & Couplings, Fluids and Filters).

We’re? committed? to our customers, who build a better world with our products, services and solutions. We understand and show the value of why they should always choose us. We’re exploring new ideas and opportunities –? innovating ?to discover the breakthroughs necessary for tomorrow’s growth.?

Through it all, we are one team ?– creating and delivering world-class components and solutions superior to the competition.?

Learn more about the Caterpillar Experience

As an Associate Data Scientist, you will leverage your quantitative analysis, data management, modeling and/or data visualization skills as an individual contributor to project teams tasked with solving business problems. This position is a part of the Caterpillar Inventory Management Research Team, which uses quantitative methods such as business simulations, data mining, and advanced statistical techniques to solve problems.

Job duties and responsibilities may include, but are not limited to:

• Analytics-based research supporting project teams
• Statistical modeling and analysis of Caterpillar and dealer parts demand & inventory 
• Using programming languages such as Python, R, Dataiku or SAS and apply machine learning models to research solutions to business problems
• Improvement of existing and development of new inventory optimization techniques
• Execution and analysis of inventory management simulations
• Ad-hoc data analysis, data processing, and data visualization
• Developing/refining large-scale solutions to fit complex situations in multiple unique environments
• Building familiarity with Inventory Management system functionality and parts management practices
• Effective communication of complex concepts and solutions to stakeholders & internal customers

Basic Qualifications:

• Bachelor’s degree completed on or before May 2023, in an Industrial Engineering, Supply Chain Management, Data Science, Business Analytics, Mathematics, Statistics, Computer Science, Economics, Business, or Related Degree Program with quantitative and technically challenging coursework
• Minimum 2.8/4.0 Cumulative Grade Point Average (no rounding) at current institution

Top Candidates Will Also Have:

• Knowledge of basic statistical approaches and/or data management techniques
• Background in data science software such as Python or R utilizing machine learning models
• Demonstrates the ability to communicate effectively verbally and with digital media
• Demonstrates the ability to effectively communicate concepts using data visualization
• Enthusiasm for big data processing, research, analytics, and problem solving 
• Demonstrates teamwork, initiative, and interpersonal skills
• Highly proficient written and verbal communication skills