Autonomy AI Lead for Data Science Pods

Caterpillar; Irving (TX); On-site; USD 98,000 - 158,000; Full time

Benefits offered by this job

Medical, dental, and vision benefits

Paid time off

401(k) savings plans

Health Savings Account

Flexible Spending Accounts

Career Development

Incentive bonus

Parental leave

Tuition Reimbursement

Job summary

Caterpillar is seeking a Data Science Pod Lead in Irving, TX to guide a multidisciplinary team of data scientists, ML engineers, and analysts. You will translate product goals into actionable technical plans, mentor the pod, and collaborate with AI Product Owners, Architects, and engineers to deliver measurable business value.

Key focus areas include enabling AI tooling within development workflows, monitoring adoption and productivity metrics, and shaping enterprise AI enablement.

Qualifications

• Experience leading multi-disciplinary data teams.
• Experience with AI/GenAI concepts and responsible AI.
• Experience in Agile teams and product ownership.
• Ability to translate business strategy into product goals.

Responsibilities

• Lead the Agentic Services & Metrics pod, delivering scalable AI enablement and analytics.
• Drive adoption of AI-assisted engineering tools to boost developer productivity.
• Partner with users and engineering teams to deploy and optimize AI tooling.
• Plan and execute pod work, balancing enablement, analytics, and delivery commitments.
• Report actionable insights on AI tool effectiveness and user engagement.
• Provide technical leadership, coaching, and mentorship across data science and software engineering.
• Stay current with AI advancements and define future services as adoption grows.

Skills

Prompt engineering

AI product acumen

Data-informed decision making

Leadership and mentoring

Software development lifecycle

Job description

Caterpillar is seeking a Data Science Pod Lead in Irving, TX to guide a multidisciplinary team of data scientists, ML engineers, and analysts. You will translate product goals into actionable technical plans, mentor the pod, and collaborate with AI Product Owners, Architects, and engineers to deliver measurable business value.

Key focus areas include enabling AI tooling within development workflows, monitoring adoption and productivity metrics, and shaping enterprise AI enablement.