Data Scientist, eCommerce Analytics

Caterpillar•Chicago, IL

3d•Onsite

About The Position

As a Data Scientist in the aftermarket analytics team, you will drive parts and services growth by building data-driven solutions that enhance digital products and customer experiences. You will apply analytics and machine learning to solve complex problems, with a focus on personalization and recommendations. You will partner with cross-functional teams, owning components of projects end-to-end while contributing to high-impact solutions that deliver measurable business value. Cat Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry leading digital solutions for our customers and dealers. With over 1.5 million connected assets worldwide, our teams use data, technology, advanced analytics, telematics, and AI capabilities to help our customers build a better, more sustainable world.

Requirements

Analytical Thinking: Extensive ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems; Knowledge of techniques and tools that promote effective analysis.
Data Cleaning, Analysis, and Preparation: Working knowledge in conducting exploratory data analysis to extract meaningful patterns, trends, and insights from complex datasets, including data mining and cleaning initiatives and writing, debugging and implementing queries involving multiple tables or databases.
Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services. Experience completing specific tasks and initiatives utilizing machine learning technologies, such as classification, regression, or optimization and specific tools and techniques to process descriptive and inferential statistics.
Programming Languages: Experience and fluency with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
Collaboration & Effective Communication: Experience working closely with cross-functional teams, providing data-driven insights and collaborating on projects to solve business challenges.

Nice To Haves

Bachelors, Masters, or PhD degree in statistics, economics, mathematics, data science or similar degree
Experience utilizing quantitative analysis, or a Master’s degree or PhD in related field
Experience in eCommerce and/or digital products domains
Experience with advanced data analysis and statistical methods including regression and hypothesis testing
Practical applications of machine learning techniques, including Collaborative Filtering, Clustering, and emerging GenAI techniques
Strong technical and problem-solving skills and evidence of continuous learning in the analytics field
Experience leading analytics projects connecting data from various business domains and providing forecasts and insights to run the business profitably
Experience with cloud technologies (AWS, Azure, Snowflake, Google Cloud, etc.)

Responsibilities

Apply machine learning, statistical modeling, causal inference, and emerging GenAI techniques to understand customer behavior and deliver recommendation and personalization solutions that drive measurable business value
Develop and deploy data-driven solutions that optimize digital experiences, including recommendation systems and AI-powered assistants (e.g., conversational insights, targeting, and sales enablement use cases)
Partner with product, engineering, and business stakeholders to translate business problems into scalable analytical and AI-driven solutions
Own components of analytics and data science projects end-to-end, from exploration and modeling to delivering production-ready insights or features
Demonstrate strong initiative to research and apply new techniques, including GenAI approaches, to improve customer impact
Communicate findings clearly to technical and non-technical audiences, influencing decisions through data-driven storytelling