Job Summary
We are seeking a Data Scientist I - Agentic Services Pod Member to help business teams understand, adopt, and maximize the value of Generative AI (GenAI) tools and agentic capabilities. This individual contributor role focuses on identifying business opportunities, translating business needs into practical AI use cases, supporting experimentation and adoption, and connecting users with approved enterprise tools, platforms, and specialist resources. The ideal candidate combines foundational knowledge of AI and GenAI with strong communication, problem-solving, and collaboration skills. The role involves working closely with business stakeholders, the Data Science Pod Lead, AI Product Owners, AI Architects, platform teams, and governance partners to support responsible AI adoption aligned with enterprise standards, security requirements, and Responsible AI principles. The position is onsite in Irving, Texas.
Key Responsibilities
• Partner with business stakeholders to identify business problems, user needs, process improvement opportunities, and potential applications of GenAI and agentic capabilities.
• Collaborate with the Data Science Pod Lead to align business engagement and enablement activities with team priorities, governance requirements, and expected outcomes.
• Work with AI Product Owners and business teams to define use cases, desired outcomes, adoption barriers, success measures, and business value.
• Evaluate opportunities from business, technical, data, risk, governance, adoption, and support perspectives.
• Explore and recommend suitable approaches, including enterprise AI tools, configurable agents, reusable patterns, workflow improvements, and specialist delivery support.
• Configure, test, demonstrate, troubleshoot, and document prompts, assistants, agents, workflows, and related user experiences.
• Apply prompt design, system instructions, knowledge grounding, structured outputs, agent configuration, and evaluation techniques.
• Explain GenAI concepts, capabilities, limitations, risks, and appropriate use cases to technical and non-technical audiences.
• Guide users on responsible AI usage, human oversight, approved tools, enterprise guidance, and available learning resources.
• Investigate user issues involving prompt behavior, AI-generated outputs, access, configurations, knowledge grounding, compatibility, workflows, and integrations.
• Use diagnostics, logs, feedback, test cases, documentation, and platform guidance to troubleshoot issues and engage specialist teams when needed.
• Document issues, resolutions, workarounds, lessons learned, and reusable guidance to improve enterprise adoption.
• Collaborate with architecture, platform, data, engineering, cybersecurity, legal, privacy, Responsible AI, learning, and change-management teams as required.
• Support experimentation, validation, adoption, and continuous improvement of AI-enabled business solutions.
Required Qualifications
• Bachelor's degree in a relevant technical or quantitative field.
• At least 2 years of relevant professional experience; internships do not count toward the required experience.
• Working knowledge of AI, Generative AI, agentic concepts, and business productivity technologies.
• Familiarity with configuring, testing, demonstrating, troubleshooting, and documenting AI prompts, assistants, agents, or workflows.
• Understanding of prompt engineering, system instructions, knowledge grounding, agent configuration, and structured outputs.
• Digital literacy across GenAI tools, collaboration platforms, workflow tools, data sources, APIs, and basic scripting or analytical tools.
• Strong verbal and written communication skills.
• Strong problem-solving abilities, initiative, patience, and willingness to learn.
• Ability to work collaboratively with technical teams, business stakeholders, and end users.
Preferred Qualifications
• Degree in Data Science, Applied Statistics, Business Analytics, Business Intelligence, Computer Science, Engineering, Mathematics, Informatics, Information Systems, Predictive Analytics, or a related technical field.
• Experience with statistical analysis, including regression, hypothesis testing, ANOVA, and statistical process control.
• Familiarity with machine learning techniques such as clustering, logistic regression, decision trees, Random Forests, Support Vector Machines, or neural networks.
• 2+ years of Python programming experience using libraries such as NumPy, SciPy, and pandas to solve business problems.
• Experience with cloud technologies such as AWS, Microsoft Azure, or Google Cloud.
• Experience in heavy equipment, automotive, aerospace, engines, transmissions, construction, mining, or other industrial environments.
• Understanding of the AI-enabled solution lifecycle, including discovery, use-case definition, experimentation, validation, approval, adoption, deployment, support, benefits measurement, and retirement.
• Familiarity with AI governance, risk reviews, documentation, testing, change management, release processes, and benefits tracking.
• Demonstrated commitment to continuous learning and applying emerging technologies to solve business challenges.
Top Three Skills
• Generative AI Tools and Agent Configuration: Ability to configure, test, demonstrate, troubleshoot, and document GenAI tools, assistants, agents, prompts, and workflows.
• Prompt Engineering and AI Evaluation: Understanding of prompt design, system instructions, knowledge grounding, structured outputs, agent configuration, evaluation, and user guidance.
• Digital and Analytical Literacy: Familiarity with collaboration platforms, workflow tools, data sources, APIs, and basic scripting or analytical tools, with deeper technical skills considered an advantage.
Key Soft Skills
• Excellent verbal and written communication.
• Strong teamwork and collaboration.
• Patience and a user-focused approach.
• Self-motivation and initiative.
• Strong analytical and problem-solving skills.
• Ability to explain technical concepts in clear, business-friendly language.
• Focus on enterprise-wide value, responsible adoption, and measurable business outcomes.
Opportunity Highlights
• Work with emerging copilots, AI agents, and Generative AI capabilities.
• Help drive enterprise-wide AI adoption and responsible AI practices.
• Collaborate with business stakeholders and cross-functional technology teams.
• Develop reusable AI adoption patterns and best practices.
• Gain exposure to diverse business functions and enterprise transformation initiatives.
