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This is an 11-week paid learning experience during which you’ll be able to connect and network with other interns and leaders within the company. We invite you to come innovate with mentors who will challenge you to develop meaningful skills. You’ll contribute your creativity and outstanding ideas, while working alongside T-Mobile employees. We’ll give you hands-on projects and the chance to create an immediate impact. As a Compensation Systems Intelligence Intern, you’ll operate at the intersection of compensation strategy, data engineering, and applied AI. This is a builder role focused on modernizing and scaling T-Mobile’s compensation analytics ecosystem through automation, structured data design, and intelligent systems. You’ll work directly with senior compensation leadership to prototype and deploy systems that reduce manual processes and enable faster, executive-ready insights. This role is ideal for someone who thrives in ambiguity, enjoys architecting solutions from the ground up, and wants hands-on experience building AI-native systems within an enterprise environment. You’ll contribute to accelerating T-Mobile’s transition toward an AI-enabled compensation operating model.
Job Responsibility:
Design and prototype structured data pipelines that unify compensation data, labor market insights, and job architecture frameworks
Build intelligent systems leveraging Enterprise GPT and retrieval-based architectures to support compensation decision-making
Automate repeatable workflows such as market pricing analysis, job evaluation insights, and executive briefing preparation
Create orchestration frameworks that standardize compensation processes and reduce operational cycle time
Integrate dashboards and reporting systems to deliver scalable, executive-ready insights with improved transparency and governance
Build Compensation Intelligence Infrastructure: Design and implement structured data pipelines connecting compensation systems and external labor market data
Develop scalable data models, query frameworks, and metadata standards to enable system interoperability
Improve data lineage, structure, and accessibility to support AI-enabled tools and reduce manual reconciliation
Develop Intelligent Systems & Workflow Automation: Prototype and deploy AI-enabled systems using Enterprise GPT and retrieval-based architectures
Automate recurring compensation workflows to improve efficiency and consistency
Design standardized orchestration frameworks that reduce operational burden and improve decision speed
Enhance Data Storytelling & Executive Insight Delivery: Integrate reporting systems using structured query layers and standardized output formats
Automate generation of executive-ready summaries from structured datasets
Improve reporting reproducibility, transparency, and scalability for senior leadership decision-making
Requirements:
Currently enrolled in a Bachelor’s or Master’s program in Computer Science, Data Science, Engineering, AI, or a related field
Strong proficiency in Python and SQL
Experience building applied AI systems (e.g., RAG, agentic workflows, LLM-based applications)
Experience in data modeling and structured pipeline design
Experience integrating APIs and enterprise datasets (preferred)
Familiarity with graph databases such as Neo4j (preferred)
Interest in workforce analytics, labor economics, or compensation strategy (preferred)
Ability to design scalable systems within enterprise constraints
Strong analytical and structured problem-solving skills
Ability to translate ambiguous business challenges into technical solutions
Clear communication skills, especially when explaining technical concepts to non-technical stakeholders
High ownership mindset with a strong builder mentality
Ability to adapt to shifting priorities and independently structure daily work
Professional collaboration with cross-functional stakeholders
At least 18 years of age
Legally authorized to work in the United States
Must be actively enrolled in a Bachelors or Graduate degree program
Nice to have:
Experience integrating APIs and enterprise datasets
Familiarity with graph databases such as Neo4j
Interest in workforce analytics, labor economics, or compensation strategy
What we offer:
Relocation assistance may be provided to program participants who reside more than 50 miles from the internship location