Data Scientist II, eCommerce Analytics

at  Caterpillar

JOB SUMMARY:

As a Data Scientist II in the aftermarket analytics team of Cat Digital, you will be tasked with enabling services growth by collaborating with other Cat Digital and business teams to maximize the value extraction of our digital products and services. With over 1.5M connected assets worldwide, our business and in the industries, we serve, data is generated continuously by Cat® equipment using the latest technology, advanced analytics, telematics and AI capabilities to help our customers build a better world.

In this position, you’ll leverage your existing expertise in data cleaning, analysis, and modeling to tackle complex problems. This role offers a perfect blend of independent work and collaboration. You’ll have the autonomy to lead specific aspects of projects while also working alongside senior team members to tackle larger challenges. We provide mentorship opportunities to help you stay current on the latest advancements in data science and refine your expertise. This individual will develop good networks within the technical community to enable technical solutions, obtain resources and cooperation needed, and remove roadblocks so that they can ensure the success of their team.

• Utilize various data science methods, such as machine learning, statistical modeling, and causal inference, to gain insights into customer behavior, optimize and personalize digital experiences, and generate measurable business value
• Coach and mentor more junior Data Scientists in the creation, validation, and application of data science methods
• Demonstrate thorough knowledge of Caterpillar Inc., its products and services, internal systems, processes, and procedures, and relevant external influences (competitors, laws and regulations, market conditions, etc.) to meet or exceed customer expectations.
• Demonstrate strong initiative to research and apply new methods to exceed customer expectations.
• Have a strong focus on continual learning in the Analytics field
• Possess thorough statistical and digital technology knowledge and the ability to solve low to medium-complexity problems.
• Have excellent communication skills, able to explain conclusions to customers with limited knowledge and experience with quantitative analytical methods.