Data Scientist

Caterpillar Inc.•Peoria, IL

9d•$97,530 - $158,480

About The Position

The Advanced Diagnostics team within the Analytics & Applied AI department of Cat Digital is looking for a talented and motivated Data Scientist to help solve business challenges using advanced analytical methods. The Data Scientist will be tasked with enabling service experiences by collaborating with other Cat Digital and Global Service business teams to maximize the value extraction of our digital products and services. The Data Scientist will be part of a team using service offerings from fluids analysis data domain (oils and coolants from equipment), as well dealer, customer, and equipment information. Candidates for this position will be expected to exhibit strong technical and communication skills, an ability to explain complex concepts and draw conclusions, present to the analytics team and leadership and business partners, a penchant for innovation, strong initiative with an ability to work independently, and interpersonal and collaboration skills.

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 (SQL), scripting languages (Python), and statistical/mathematical software packages.
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

Bachelor's degree with 5+ years with proven technical data science experience or a Master's degree with 3+ years proven technical data science experience, preferably in statistics, applied mathematics, data science, analytics, engineering, computer science, or a similar field with quantitative coursework
Proven experience using: Python for data analysis and modeling, including Jupyter Notebooks and common libraries & packages
Version control systems such as Git
Database technologies such as SQL and NoSQL
Processes large quantities of detailed information with high levels of accuracy
Practical experience with cloud computing and software development for building solutions in cloud environments (AWS, Snowflake, etc.)
Practical experience developing, deploying, and productionizing predictive and/or prescriptive analytics solutions and machine learning models
Experience with advanced data analysis and the application of machine learning and statistical techniques, including classification, regression, clustering, collaborative filtering, and hypothesis testing
Experience developing and implementing natural language processing (NLP) algorithms and models to extract insights from textual data, utilizing advanced text mining techniques
Strong technical and problem-solving skills with a focus on continual learning in the analytics field, demonstrating initiative to research and apply new methods to exceed customer expectations
Strong communication skills, with the ability to explain conclusions to technical leaders, managers, and business partners, and to collaborate effectively with team members
Experience operating in an Agile environment with ownership, initiative and the ability to complete tasks
Experience with API development to integrate with digital applications and extract and process data efficiently
Ability to work independently with strong attention to detail and a focus on delivering customer through business partner requirements
Demonstrated interest in understanding, experimenting with, or applying emerging AI and GenAI techniques to real-world data problems, with a willingness to continuously learn and adapt as the field evolves

Responsibilities

Act as a technical individual contributor on a small multi-person analytics team with work directed by the technical project leader who reviews methods and results.
A blend of independent work and collaboration with the autonomy to lead specific tasks of the project while also working alongside team members for larger challenges.
Leverage existing expertise in data cleaning, analysis, quantitative analytic methods, and modeling to tackle complex issues.
Utilize various data science methods, such as machine learning, statistical modeling, and causal inference, to gain insights, optimize, and generate measurable business value.
Become familiar with the company’s processes, products, governance and organization.
Challenges include meeting expectations in delivering results, learning to refine solutions to better fit complex situations, making timely decisions, and communicating effectively with the technical project leader, manager, and business partners.