Senior Data Scientist — AI-Driven Analytics Leader

Caterpillar Financial Services Corporation

Mossville (IL)

On-site

USD 120,000 - 180,000

Full time

3 days ago

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Job summary

Caterpillar Inc. Remanufacturing invites a Senior Data Scientist to Mossville, IL, with additional locations considered in the Midwest.

You will lead the design, development, and deployment of advanced analytics, ML, and AI-enabled solutions to solve complex remanufacturing problems. You will build analytics products and decision-support tools using Python, Kedro, dbt, Docker, AWS, Snowflake, Azure DevOps, and Power BI, partnering with stakeholders to translate needs into measurable business

Qualifications

Lead the design, development, and deployment of advanced analytics, machine learning, and AI-enabled solutions that solve complex business problems across the Reman Division.

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.