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Senior Data Scientist
Caterpillar Inc.. Lead design, development, and deployment of advanced analytics, machine learning, and AI-enabled solutions across the Reman Division .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying advanced analytics and machine learning solutions using Python, with a strong focus on model validation, operationalization, and best practices in data science. Proficient in collaborating with stakeholders to translate business needs into actionable insights and analytical products.
Highest-signal resume keywords
Python DevelopmentMachine Learning SolutionsData Science Best PracticesAWS and Azure DevOpsPower BI Reporting
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical ModelingOptimizationForecastingSimulationFeature EngineeringModel EvaluationGenerative AI ApplicationsData Quality PracticesELT/ETL PatternsAnalytical Thinking
Soft Skills
CommunicationMentoringAnalytical Problem Solving
Tools & Technologies
KedroDbtDockerSnowflakeGit
Industry Keywords
AI-Enabled SolutionsNatural Language InterfacesData Engineering ConceptsModel DocumentationAutomated Testing
Tech Stack
Tools & technologiesAWSAzureDockerETLPython
About the role
Key responsibilities & impact- Lead design, development, and deployment of advanced analytics, machine learning, and AI-enabled solutions across the Reman Division
- Apply statistical modeling, machine learning, optimization, forecasting, simulation, and experimentation
- Develop, validate, and operationalize descriptive analytics and predictive models using Python
- Build analytics products and decision-support tools with machine learning outputs, curated data assets, and Power BI reporting
- Partner with business stakeholders to frame analytical problems, define success measures, translate requirements, and communicate insights
- Research, prototype, and implement generative AI, intelligent agents, natural language interfaces, and automation
- Use Python, Kedro, dbt, Docker, AWS, Snowflake, and Azure DevOps to create governed, production-ready workflows
- Collaborate with data engineering and platform partners on data pipelines, semantic models, data quality frameworks, and governed data products
- Establish 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
- Mentor team members on data science, machine learning, AI development, and analytics engineering
- Promote reusable, standardized analytical product development and reduce technical debt
- Define standards for model documentation, metadata management, knowledge sharing, monitoring, and operational supportability
Requirements
What you’ll need- 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
- Practical experience with dbt, Kedro, AWS, Docker, Snowflake, Azure DevOps, Git, and Power BI
- Ability to translate ambiguous business needs into structured analytical approaches and communicate insights clearly
- Working knowledge of data engineering concepts, ELT/ETL patterns, data modeling, and data quality practices
- Knowledge of business statistics, analytical thinking, machine learning, programming languages, query and database access tools, and requirements analysis
- Must pass background screening
- Must pass drug and alcohol screening
- Visa sponsorship is not available
- Must be eligible to work without employer-specific sponsorship
Benefits
Comp & perks- Potential annual bonuses
- Paid vacation days
- Paid holidays
- 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)
- Domestic relocation assistance
- Career Development
- Incentive bonus
- Employee Discounts
- Adoption benefits
- Tuition Reimbursement