Data Science AI Pod Member

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Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar yourejoining a global team who cares not just about the work we do but also about each other. We are the makers problem solvers and future world builders who are creating stronger more sustainable communities. We dontjust talk about progress and innovation here we make it happen with our customers where we work and live. Together we are building a better world so we can all enjoy living in it.

Job Description Summary

The Data Science Pod Member is an individual contributor responsible for designing developing validating and deploying data science and AI solutions as part of a multidisciplinary pod. This role focuses on hands-on analytical modeling and engineering work translating business and product objectives into highquality technical deliverables. Pod Members collaborate closely with the Data Science Pod Lead AI Product Owner AI Architects and engineering partners to deliver measurable value while adhering to enterprise standards and Responsible AI principles.

Role Definition

Responsibilities

Data Science & Solution Development

• Design build test and iterate on data science machine learning and Generative AI (GenAI) solutions aligned to pod objectives including LLMbased systems retrievalaugmented generation (RAG) agents and multimodal use cases.
• Perform data exploration feature engineering model training evaluation and validation including GenAIspecific evaluation (e.g. groundedness hallucination risk latency cost and quality metrics).
• Implement solutions that are scalable maintainable and aligned with enterprise architecture data and engineering standards with explicit consideration for GenAI safety security and Responsible AI controls (prompt management guardrails data provenance and access controls).
• Contribute productionready code notebooks pipelines and model artifacts including prompts system instructions evaluation harnesses and GenAI configuration assets.

Delivery & Execution

• Execute assigned work items to meet sprint and increment commitments aligned to the product roadmap.
• Balance experimentation with delivery supporting the transition from proofofconcept to production.
• Identify and communicate technical risks assumptions data limitations and tradeoffs to the Pod Lead.
• Support operational readiness through testing documentation and handover activities.

Collaboration & Ways of Working

• Work closely with the Data Science Pod Lead to align technical work with podlevel direction and priorities.
• Partner with AI Product Owners to understand business problems success metrics and value hypotheses.
• Collaborate with platform data engineering MLOps and software engineering teams.
• Communicate analytical findings model behavior and recommendations to both technical and nontechnical stakeholders.

Quality Governance & Responsible AI

• Ensure models and analytics meet quality performance security reliability and compliance standards.
• Apply Responsible AI principles throughout the solution lifecycle.
• Produce and maintain appropriate technical documentation experiments and traceability artifacts.

Continuous Improvement & Innovation

• Stay current with advances in data science ML and Generative AI techniques.
• Contribute ideas to improve tools processes and reusable assets across the data science practice.
• Participate in communities of practice knowledge sharing and peer reviews

Degree Requirement

Bachelors degree in engineering computer science data science mathematics statistics or a related field (or equivalent practical experience). Advanced degree (Masters or PhD) in artificial intelligence machine learning engineering mathematics physics or a closely related field is considered an advantage.

Skill Descriptors

• Data Science & ML Foundations :Handson experience applying statistical analysis machine learning and/or Generative AI techniques to realworld problems.
• Programming & Tooling: Proficiency in relevant programming languages and tools (e.g. Python SQL notebooks ML frameworks); ability to write test debug and maintain productionquality code.
• DataInformed Problem Solving: Ability to analyze data experiments and model performance metrics to generate insights and guide technical decisions.
• Agile Delivery: Experience working in Agile teams contributing to sprint planning estimation and iterative delivery.
• Communication & Collaboration: Clear verbal and written communication skills with the ability to explain technical concepts and analytical results to diverse audiences..

Level Working Knowledge

• Identifies and documents specific problems and potential analytical or modeling approaches.
• Examines problems from multiple stakeholder perspectives.
• Develops and evaluates alternative techniques for assessing accuracy relevance and performance.
• Uses appropriate fact finding techniques diagnostics and experimentation

Software Development Life Cycle

• Knowledge of the software development life cycle
• Ability to work within a structured methodology for delivering and maintaining data science and AI solutions including development testing deployment and support

Artificial Intelligence

• Knowledge of AI and Generative AI concepts risks and opportunities; ability to govern and guide AI product development to achieve business outcomes while adhering to responsible AI principles.
• Explains the methodology and technologies of artificial intelligence.
• Describes the concepts functions and features of artificial intelligence (AI).
• Locates relevant resources to obtain the latest information on artificial intelligence.
• Cites examples of successful implementation of AI technologies and systems.

Programming

Knowledge of relevant programming languages and tools; ability to test write design debug troubleshoot and maintain source codes and computer programs.

• Prompt engineering
• Programming literacy in AI related languages (eg. Python R etc)

Technical Troubleshooting

Knowledge of technical troubleshooting approaches tools and techniques; ability to anticipate recognize and resolve technical issues on hardware software application or operation.

• Discovers analyzes and resolves hardware software or application problems.
• Works with vendor-specific diagnostic guides tools and utilities.
• Handles calls related to product features applications and compatibility standards.
• Analyzes code logs and current systems as part of advanced troubleshooting.
• Records and reports specific technical problems solving processes and tools that have been used.

Note:
This Job Description is intended as a general guide to the job duties for this position and is intended for the purpose of establishing the specific salary grade. It is not designed to contain or be interpreted as an exhaustive summary of all responsibilities duties and effort required of employees assigned to this job. At the discretion of management this description may be changed at any time to address the evolving needs of the organization. It is expressly not intended to be a comprehensive list of essential job functions as that term is defined by the Americans with Disabilities Act.

Posting Dates:

Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply

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