AI Adoption Strategy Intern (Analytics)

Lockheed Martin•Fort Worth, MD

21h•$58,552 - $77,788•Remote

About The Position

By bringing together people that use their passion for purposeful innovation, at Lockheed Martin we keep people safe and solve the world's most complex challenges. Our people are some of the greatest minds in the industry and truly make Lockheed Martin a great place to work. With our employees as our priority, we provide diverse career opportunities designed to propel development and boost agility. Our flexible schedules, competitive pay, and comprehensive benefits enable our employees to live a healthy, fulfilling life at and outside of work. At Lockheed Martin, we place an emphasis on empowering our employees by fostering innovation, integrity, and exemplifying the epitome of corporate responsibility. Lockheed Martin’s Enterprise Operations & AI Adoption Strategy team is at the forefront of shaping how generative‑AI tools are used across the enterprise. By joining us you will work side‑by‑side with senior AI strategists, software engineers, product managers, and business leaders to accelerate AI‑driven transformation, while gaining hands‑on experience in data‑science research, analytics, and change‑management. The AI Adoption Strategy team partners with developers, engineering leaders, and enterprise stakeholders to: - Identify high‑impact use‑cases for generative‑AI developer tools. - Design and deliver enablement programs (workshops, tutorials, videos). - Track adoption metrics, gather feedback, and produce executive‑ready insights. - Champion AI ethics, security, and trust throughout the development lifecycle. The intern will support these efforts by providing data‑driven research, analytics, and prototype visualizations that help the team prioritize initiatives and demonstrate ROI.

Requirements

Pursuing a bachelor's degree in applied mathematics/statistics, computer science, data science, information systems/business analytics
Demonstrated experience leading impactful data‑science/analytics projects (e.g., research, open‑source contributions, hackathon wins, internship deliverables) that yielded measurable outcomes.
Proficient in Python (pandas, numpy, matplotlib/seaborn) and comfortable working in Jupyter notebooks.
Familiar with generative‑AI concepts such as large‑language models and prompt engineering.
Strong analytical, problem‑solving, and data‑visualization skills.
Excellent written and verbal communication abilities.

Nice To Haves

Experience with data‑visualization libraries (Plotly, Streamlit, Power BI, Tableau).
Understanding of supervised/unsupervised learning, model evaluation metrics, and basic statistical testing.
Hands‑on exposure to OpenAI API, LangChain, Azure OpenAI, or similar generative‑AI platforms.
Familiarity with Git, GitHub Actions, and CI/CD pipelines.
Exposure to Docker, Kubernetes (basic concepts), or cloud notebooks (Azure ML, SageMaker).
Understanding of stakeholder analysis, adoption frameworks (e.g., HEART, ADKAR), or experience running workshops.
Ethics & Trust Knowledge of AI ethics, data privacy, and security best practices.

Responsibilities

Research & Landscape Analysis – Conduct literature reviews and market scans on emerging AI‑assisted development tools, prompting techniques, and workflow automation.
Data Collection & Cleaning – Aggregate usage data from internal telemetry, surveys, and community platforms; perform data wrangling, validation, and enrichment.
Adoption Metrics & Reporting – Develop dashboards (Tableau) and analytical models to track adoption trends, user engagement, and productivity gains.
Prototype Analytics – Build proof‑of‑concept scripts in Python to simulate ROI scenarios (e.g., time‑saved per line of code, defect‑rate reduction).
Stakeholder Engagement – Summarize findings for internal briefings; prepare concise executive slide decks and one‑page decision briefs.
Community Enablement – Participate in internal AI developer forums, answer data‑related questions, and help organize hackathons or “AI‑Office‑Hours” sessions.