Data Scientist (Agentic Services Pod Member) SOFTWARE ENGINEERING
Irving, Texas
Contract Oct 14, 2026
Data Scientist (Agentic Services Pod Member) Irving, TX | Onsite | 12 Months Job Details
Estimated Start Date: November 9, 2026
Building Location: TX – Irving
Work Arrangement: On-Site Full Time; first shift
Duration: 12 months
Full Job Description
JOB PURPOSE:
The Agentic Services Pod Member is an individual contributor responsible for helping business teams understand, adopt, and gain value from Generative AI tools and agentic capabilities. This role works directly with business partners to identify suitable opportunities, translate business needs into practical use cases, guide teams through experimentation and adoption, and connect users with approved tools, platforms, patterns, and specialist support. Pod Members collaborate closely with the Data Science Pod Lead, AI Product Owner, AI Architects, platform teams, governance partners, and business stakeholders to accelerate responsible adoption while ensuring solutions align with enterprise standards, security requirements, and Responsible AI principles.
JOB DUTIES:
The Data Scientist will participate on cross-functional project teams in order to solve a problem presented by a Business Unit or Service Organization, a Dealer, or a Customer.
The key role of this second level data scientist position is to move from learning and assisting others to learning to contribute independently. The Data Scientist I is expected to become familiar with the company’s processes, products, and organization. Work is typically directed by a project or team lead who might review both methods and results. Challenges include meeting expectations in delivering results, learning to consider alternative courses of actions, making timely decisions, developing communication skills, working with people, and pushing the technical bounds of experimentation while meeting customer commitments.
Individuals in this position might expect to have several assignments allowing them to gain experience on multiple projects. They will be expected to apply theory and concept in contributing to the solution in the assigned area.
The job function may include data collection and analysis; development, validation, application, and refinement of statistical models; application of related digital technologies in processing both the inputs and outputs from the models.
The Data Scientist I demonstrates an expanded breadth of knowledge and the ability to handle basic issues independently. They also demonstrate very good communication skills; planning and organization, teamwork, and decision making skills; a strong concern for customers; a strong focus on continual learning in the Analytics field; and has basic knowledge of our products and services.
Basic Qualifications:
• Typically requires a Bachelor’s degree, preferably in engineering, computer science, statistics, economics, mathematics, or a similar field with quantitative coursework, and 1-2 years of professional experience utilizing quantitative analysis is required, or a Master’s or PhD degree.
• Must be comfortable working in industry standard statistics, analytics, and data visualization packages.
• Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively.
Top Candidates Will Also Have:
• Bachelors, Masters, or PhD degree in Applied Statistics, Data Science, Business Analytics, Business Intelligence & Analytics, Computer Science, Computer Science + X, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), Informatics, Information Systems Management, Mathematics, MBA with Technical Undergrad, Predictive Analytics, Statistics, or equivalent technical degree.
• Experience with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc.
• Practical applications of machine learning techniques such as Clustering, Logistic Regression, CART, Random Forests, SVM or Neural Networks.
• Experience in design / development of heavy equipment (ex. automotive, aerospace, engine, transmission, construction, mining, industrial, etc)
• Strong technical and problem-solving skills and evidence of continuous learning in the analytics field
• 2+ years of experience applying python (NumPy, SciPy, pandas, etc) programming to solve business challenges
• Experience with cloud technologies (AWS, Azure, Google Cloud, etc)
• Strong initiative to research and apply new methods and digital technologies to exceed customer expectations.
• Good communication, interpersonal, and collaboration skills0-2 years experience.
Position’s Contributions to Work Group Position’s Contributions to Work Group:
Work closely with the Data Science Pod Lead to align business engagement and enablement activities with pod direction, priorities, governance, and expected outcomes.
Partner with AI Product Owners and business stakeholders to understand user needs, desired outcomes, adoption barriers, success measures, and value hypotheses.
Collaborate with AI architecture, platform, data, engineering, cybersecurity, legal, privacy, Responsible AI, learning, and change-management teams as required.
Communicate GenAI concepts, tool capabilities, limitations, risks, and recommended approaches in clear language for both technical and non-technical audiences.
Why this Role?
Work at the forefront of AI innovation using the latest copilots, agents, and GenAI capabilities while helping define enterprise-wide best practices.
Deliver impact at scale by enabling solutions that can benefit hundreds or thousands of employees rather than a single team or project.
Enjoy a unique blend of technology and business engagement, combining AI expertise, consulting, facilitation, change management, and problem solving.
Create reusable assets and best practices that enable others to succeed, multiplying your impact far beyond your own projects.
Learn continuously through exposure to diverse business functions, emerging AI technologies, and enterprise transformation initiatives.
Typical Day or Week in the Role Typical task breakdown:
Identifies and documents business problems, user needs, process opportunities, and potential applications of GenAI tools or agentic capabilities.
Examines opportunities from user, business value, data, risk, governance, technology, adoption, and support perspectives.
Develops and evaluates alternative approaches, including use of existing enterprise tools, configurable agents, reusable patterns, process changes, or referral to specialist delivery teams.
Uses appropriate discovery, fact-finding, facilitation, experimentation, feedback, and evaluation techniques to guide recommendations and adoption decisions.
Interaction with team:
Works with users to reproduce issues, clarify expected outcomes, and distinguish between user guidance, configuration, data, platform, or integration problems.
Uses available diagnostics, logs, feedback, test cases, documentation, and platform guidance to investigate issues and engage specialist teams when needed.
Supports questions related to GenAI tool features, prompt behavior, knowledge grounding, access, compatibility, workflow design, and appropriate usage.
Analyzes prompts, configurations, outputs, user feedback, and available system information as part of structured troubleshooting.
Records and communicates issues, resolution steps, workarounds, lessons learned, and reusable guidance to improve adoption and support.
Working knowledge of relevant GenAI tools and business productivity technologies; ability to configure, test, demonstrate, troubleshoot, and document prompts, assistants, agents, workflows, and related user experiences.
Prompt design, system instructions, knowledge grounding, agent configuration, structured outputs, evaluation, and user guidance.
Digital literacy across GenAI tools, collaboration platforms, workflow tools, data sources, APIs, and basic scripting or analytical tools, with deeper technical skills considered an advantage.
Additional Technical Skills (Required)
Knowledge of AI, Generative AI, and agentic concepts, risks, opportunities, and limitations; ability to guide responsible application of these technologies to achieve business outcomes.
Explains GenAI and agentic concepts, common use cases, tool capabilities, limitations, and the role of human oversight in clear business language.
Describes how copilots, assistants, agents, knowledge grounding, prompts, and AI-enabled workflows can support business activities.
Locates and evaluates relevant enterprise guidance, learning resources, approved tools, examples, and specialist support for business users.
Shares practical examples and reusable patterns that help business teams adopt GenAI tools responsibly and effectively.
(Desired)
Knowledge of the lifecycle for AI-enabled business solutions, including discovery, use-case definition, experimentation, validation, approval, adoption, deployment, support, measurement, and retirement.
Ability to work within structured delivery and governance methods for GenAI solutions, including intake, prioritization, documentation, testing, risk review, change management, release, support, and benefits tracking.