Data Scientist II

Key Skills

Python Programming, SQL, Cloud computing

Job Description

Caterpillar Inc. is more than big, heavy equipment and much more than yellow iron. Our products have evolved from simple mechanical workhorses to sophisticated, electronically controlled work-site solutions. This transformation along with our smart factories and our integrated dealer network has wealth of data ready to be harvested to open new markets, fine tune our processes or deliver differentiated customer solutions. Analytics Professionals are the data driven, business professionals providing solutions to all areas across the Caterpillar enterprise.

Marketing & Branding Analytics uses quantitative methods such as business simulations, data mining, and advanced statistical techniques to solve marketing challenges for internal and external Caterpillar customers. The Data Scientist II contributes to this mission by leveraging his or her quantitative analysis, data management, modeling and/or data visualization skills as an individual contributor to project teams tasked with solving business problems.

JOB DUTIES:

• Caterpillar uses quantitative techniques to solve problems. Typical problems include enhancing customer satisfaction by delivering key insights on customer experience, identifying sales, rental, and service opportunities for Caterpillar dealers, determining the principal drivers to maximize marketing return on investment; recommending optimum investment in each marketing channel.
• The principal responsibility of the Data Scientist II is to be an independent contributor to multi-person analytic teams. This position has a depth of knowledge in quantitative analytic methods, data management, and or associated digital technologies suitable to handle all but the most complex issues. Senior Data Analysts are expected to be familiar with the company’s processes, products, and organization, as well as its customers, competitors, and stakeholders. Work is typically directed by a direct supervisor, project or team lead through a review of results. Decisions on routine, medium risk issues that may affect the project team, suppliers or internal customers may be made by this position. Challenges include meeting expectations in delivering results, learning to refine solutions to better fit complex situations, making timely decisions, and communicating effectively with all project stakeholders. The Data Scientist II also mentors and develops the capabilities and organizational knowledge of more junior data scientists and associates.
• The Data Scientist II demonstrates thorough knowledge of statistical approaches, data management techniques, and/or related digital technologies, and the ability to handle complex issues. The incumbent demonstrates very good communication and presentation skills, being able to explain conclusions to customers who have limited knowledge and experience with quantitative analytical methods. As an individual contributor on teams, they should also exhibit strong initiative and teamwork skills, and a comprehensive knowledge of Caterpillar Inc., its products and services; its internal systems, processes, and procedures; and the external environment in which it competes.

• BACKGROUND/EXPERIENCE: Typically requires a Bachelor’s degree, preferably in statistics, economics, mathematics, or a similar field with quantitative coursework, and 4-5 years of marketing analytics experience utilizing quantitative analysis, a Master’s degree and 2-3 years of experience, or a PhD in one of the associated fields. Incumbent will have exhibited the ability to work on increasingly more complex assignments and will have demonstrated teamwork, initiative, interpersonal skills, and the ability to communicate effectively. In addition to 2-4 years experience with Caterpillar, working with a different unit or working with different products, processes or systems is desirable. Must be comfortable working in MS Office, and industry standard statistics and data visualization packages such as SAS, R, Python, Tableau and Power BI. Candidate to have exposure on handing data in cloud environment such as Snowflakes, Google Cloud Platform etc.