Senior Data Scientist

Caterpillar Inc. • Mossville, IL

19h • $112,710 - $183,140 • Onsite

About The Position

Caterpillar’s Remanufacturing Division is looking for a Senior Data Scientist. Primary location for this position will be Mossville, IL. Additional locations to be considered: Franklin, IN, Corinth, MS, Fargo, ND, & Irving, TX.

This position requires working onsite five days a week.

Requirements

• Bachelor’s degree in Engineering, Computer Science, or other Technical field; or proven work experience
• Hands-on experience developing data science and machine learning solutions using Python, including model development, validation, deployment, monitoring, and continuous improvement.
• Strong understanding of supervised and unsupervised learning, forecasting, optimization, statistical analysis, feature engineering, model evaluation, and practical application of ML techniques to business problems.
• Experience building AI-enabled solutions, including generative AI applications, natural language solutions, intelligent agents, or automation tools that improve analytical workflows and business decision-making.
• Practical experience with modern analytics and development tools such as dbt, Kedro, AWS, Docker, Snowflake, Azure DevOps, Git, and Power BI.
• Ability to translate ambiguous business needs into structured analytical approaches, communicate insights clearly, and deliver solutions that are adopted and sustained by the business.
• Working knowledge of data engineering concepts, ELT/ETL patterns, data modeling, and data quality practices needed to support reliable analytical and machine learning solutions.
• Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions.
• Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.
• Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
• Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
• Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.
• Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.
• Requirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.

Nice To Haves

• Level Working Knowledge: Explains the basic decision process associated with specific statistics.
• Works with basic statistical functions on a spreadsheet or a calculator.
• Explains reasons for common statistical errors, misinterpretations, and misrepresentations.
• Describes characteristics of sample size, normal distributions, and standard deviation.
• Generates and interprets basic statistical data.
• Level Extensive Experience: Evaluates and makes contributions to best practices.
• Processes large quantities of detailed information with high levels of accuracy.
• Productively balances speed and accuracy.
• Employs techniques for motivating personnel to meet or exceed accuracy goals.
• Implements a variety of cross-checking approaches and mechanisms.
• Demonstrates expertise in quality assurance tools, techniques, and standards.
• Level Working Knowledge: Approaches a situation or problem by defining the problem or issue and determining its significance.
• Makes a systematic comparison of two or more alternative solutions.
• Uses flow charts, Pareto charts, fish diagrams, etc. to disclose meaningful data patterns.
• Identifies the major forces, events and people impacting and impacted by the situation at hand.
• Uses logic and intuition to make inferences about the meaning of the data and arrive at conclusions.
• Level Working Knowledge: Completes specific tasks and initiatives utilizing machine learning technologies, such as search engine optimization.
• Utilizes specific tools and techniques to process descriptive and inferential statistics.
• Applies specific computing languages and tools in machine learning, such as R and Python.
• Explores to use machine learning in one own areas to make business improvements.
• Conducts data mining and cleaning initiatives.
• Level Working Knowledge: Participates in the implementation and support of specialized programming languages.
• Conducts basic reviews on writing a specific programming language within a specific platform.
• Assists with the design and development of specialized programming languages.
• Follows an organization's standards, policies and guidelines for structured programming specifications.
• Diagnoses and reports minor or routine programming language problems.
• Level Extensive Experience: Writes, debugs and implements complex queries involving multiple tables or databases.
• Works with aggregate functions, complex joins, groupings, dynamic and embedded SQL's (Structured Query Languages).
• Teaches others about query optimization techniques and facilities.
• Consults on query optimization, interactive queries, testing and verification.
• Evaluates all major database access tools and functions for distributed databases.
• Compares and contrasts the benefits and drawbacks of various SQL products.
• Level Working Knowledge: Follows policies, practices and standards for determining functional and informational requirements.
• Confirms deliverables associated with requirements analysis.
• Communicates with customers and users to elicit and gather client requirements.
• Participates in the preparation of detailed documentation and requirements.
• Utilizes specific organizational methods, tools and techniques for requirements analysis.

Responsibilities

• Lead the design, development, and deployment of advanced analytics, machine learning, and AI-enabled solutions that solve complex business problems across the Reman Division.
• Apply statistical modeling, machine learning techniques, optimization methods, forecasting, simulation, and experimentation to identify opportunities, improve decisions, and deliver measurable business value.
• Develop, validate, and operationalize descriptive analytics and predictive models using Python and modern data science practices while ensuring solutions are explainable, maintainable, and aligned to business objectives.
• Build analytics products and decision-support tools that combine machine learning outputs, curated data assets, and intuitive Power BI reporting to improve adoption and business actionability.
• Partner with business stakeholders to frame analytical problems, define success measures, translate business requirements into data science solutions, and communicate insights to technical and non-technical audiences.
• Research, prototype, and implement emerging AI development approaches, including generative AI, intelligent agents, natural language interfaces, and automation opportunities that improve business processes and analytical productivity.
• Use python, Kedro, dbt, Docker, AWS, Snowflake, Azure DevOps, and related tools to create repeatable, governed, and production-ready analytical workflows that support model development, deployment, and monitoring.
• Collaborate with data engineering and platform partners to ensure required data pipelines, semantic models, data quality frameworks, and governed data products are available to support scalable analytical solutions.
• Establish and promote data science best practices including source control, code review, automated testing, experiment tracking, model documentation, reproducible pipelines, and deployment standards.
• Lead Agile planning, analytical design reviews, model review discussions, and project execution efforts while mentoring team members on data science, machine learning, AI development, and analytics engineering practices.
• Champion sustainable analytical product development by reducing technical debt, improving reusability, and promoting standardized approaches across the Reman Analytics organization.
• Define and execute standards for model documentation, metadata management, knowledge sharing, monitoring, and operational supportability to improve long-term maintainability of analytical solutions.

Benefits

• total rewards package that provides day one benefits along with the potential of annual bonuses.
• paid vacation days and paid holidays (prorated based upon hire date).
• Medical, dental, and vision coverage
• Paid time off plan (Vacation, Holiday, Volunteer, Etc.)
• 401k savings plan
• Health savings account (HSA)
• Flexible spending accounts (FSAs)
• Short and long-term disability coverage
• Life Insurance
• Paid parental leave
• Healthy Lifestyle Programs
• Employee Assistance Programs
• Voluntary Benefits (Ex. Accident, Identity Theft Protection)
• Medical, dental, and vision benefits
• Paid time off plan (Vacation, Holidays, Volunteer, etc.)
• 401(k) savings plans
• Health Savings Account (HSA)
• Flexible Spending Accounts (FSAs)
• Health Lifestyle Programs
• Employee Assistance Program
• Voluntary Benefits and Employee Discounts
• Career Development
• Incentive bonus
• Disability benefits
• Life Insurance
• Parental leave
• Adoption benefits
• Tuition Reimbursement

What This Job Offers

• Job Type: Full-time
• Career Level: Senior