Senior AI-Driven Measurement & Analytics Scientist

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

Benefits offered by this job

Bus pass

Tuition benefits

Retirement plan

Life insurance

Job summary

Carnegie Mellon University’s Software Engineering Institute (SEI) in Pittsburgh, PA, seeks a data scientist to lead analytic projects, refine workflows, and deliver actionable insights to decision-makers. You will build tools and data pipelines, applying statistical modeling and ML to real-world datasets, while collaborating with experts across domains.

The role emphasizes reproducible analytics, modern data engineering practices, and the exploration of open‑source SLM and generative AI tools to

Qualifications

• BS/MS/PhD in data science, statistics, ML, CS, or quantitative field with substantial experience.
• Proficiency in statistical modeling and data science using R or Python.
• Experience with Linux/Unix, containerization, or modern data engineering tools; willingness to learn.
• Strong communication skills and ability to present analytic concepts to expert and non‑expert audiences.

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 complex real‑world data, 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 to data pipelines, infrastructure, and operational analytics to ensure reliability, reproducibility, and trustworthy measurement.
• Work with modern infrastructure tooling and learn new technologies as needed 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

Statistical modeling

Data science

R/Python

Linux/Unix

Containerization

Communication skills

Travel readiness

Causal inference concepts

Education

BS with 10+ years in data science/quantitative field

MS with 8+ years in data science/quantitative field

PhD with 5+ years in data science/quantitative field

Tools

R

Python

Shiny or Dash

Containerization

Linux/Unix

Job description

Carnegie Mellon University’s Software Engineering Institute (SEI) in Pittsburgh, PA, seeks a data scientist to lead analytic projects, refine workflows, and deliver actionable insights to decision-makers. You will build tools and data pipelines, applying statistical modeling and ML to real-world datasets, while collaborating with experts across domains.

The role emphasizes reproducible analytics, modern data engineering practices, and the exploration of open‑source SLM and generative AI tools to