Senior Applied Measurement & AI Analytics Leader

Software Engineering Institute | Carnegie Mellon University; Pittsburgh (Allegheny County); On-site; USD 140,000 - 190,000; Full time

Job summary

The Software Engineering Institute (SEI) at Carnegie Mellon University seeks a seasoned data scientist to lead analytic projects that fuse statistical modeling, ML, and data engineering. You will design measurement workflows, build analytic tools, and deliver insights to decision‑makers across government and industry.

Collaborate with engineers, mission operators, and domain experts to ensure trustworthy analytics, reproducible results, and scalable data pipelines.

Qualifications

• BS with 10+ years, MS with 8+ years, or PhD with 5+ years in data science, statistics, machine learning, computer science, or another quantitative field.
• Proficiency in statistical modeling and data science using R or Python.
• Experience with Linux/Unix, containerization, or modern data engineering tools, or willingness to learn.
• Strong communication skills and ability to present analytic concepts to expert and non‑expert audiences.
• Willingness to travel (up to ~25%) to CMU/SEI sites, customer locations, and conferences.
• You will be subject to a background investigation and must be able to obtain/maintain a DoD security clearance.

Responsibilities

• Lead analytic projects, including scoping work, and AI/ML enabled designing analytical approaches, coordinating interdisciplinary contributors, managing timelines, and ensuring high‑quality technical outcomes that meet mission and engineering needs.
• Collaborate on multi‑disciplinary efforts, refining workflows, building tools, and integrating statistical, machine‑learning, and small‑language‑model results into operational decision‑making.
• Apply statistical modeling, ML and data science methods to real‑world datasets, guiding customers in interpreting results and incorporating insights into decisions.
• Build, maintain, and enhance analytic software tools including R/Python dashboard applications, analysis environments, automated AI/ML workflows, and robust data pipelines.
• Apply engineering discipline and scientific rigor to data pipelines, infrastructure, and operational analytics to ensure reliability and reproducibility.
• Work with modern infrastructure tooling and learn new technologies to ensure analytic systems operate smoothly and securely.
• Explore and apply open‑source small‑language model (SLM) and generative AI tools to enhance analytic workflows.
• Contribute to research papers, technical writing, outreach materials, and present findings to conferences, workshops, internal teams, government customers, and senior leaders.

Skills

Communication skills

Travel readiness

Analytic leadership

Collaborative teamwork

Problem solving

Education

Bachelor's degree

Master's degree

PhD

Tools

R

Python

Linux/Unix

Containerization

Databases

CI/CD tooling

Job description

The Software Engineering Institute (SEI) at Carnegie Mellon University seeks a seasoned data scientist to lead analytic projects that fuse statistical modeling, ML, and data engineering. You will design measurement workflows, build analytic tools, and deliver insights to decision‑makers across government and industry.

Collaborate with engineers, mission operators, and domain experts to ensure trustworthy analytics, reproducible results, and scalable data pipelines.