Senior Data Scientist: Causal ML, Dashboards & Pipelines

Software Engineering Institute | Carnegie Mellon University; Pittsburgh (Allegheny County); On-site; USD 130,000 - 210,000; Full time

Job summary

Carnegie Mellon University’s Software Engineering Institute (SEI) seeks a senior data scientist to lead analytic projects at the intersection of statistics, data engineering, and AI-enabled analytics in support of government and industry missions.

You will build measurement workflows, develop analytic tools (R/Python dashboards), and mentor teams while partnering with domain experts to shape evidence-based decisions for high-impact outcomes.

Qualifications

• Advanced degree in data science, statistics, computer science, or a related quantitative field.
• Proficiency in statistical modeling and data science using R or Python.
• Experience with Linux/Unix and containerization; willingness to learn modern data engineering tools.
• Strong communication skills and ability to present analytic concepts to technical and non-technical audiences.
• Willingness to travel (up to ~25%) to CMU/SEI sites and conferences.
• Background investigation and ability to obtain DoW security clearance.

Responsibilities

• Lead analytic projects, including scoping work and AI/ML-enabled design of analytical approaches, coordinating interdisciplinary contributors, managing timelines, and ensuring high-quality technical outcomes.
• Collaborate on multi-disciplinary efforts to refine workflows, build tools, and integrate statistical, ML, 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 informing decisions.
• Build, maintain, and enhance analytic software tools including R/Python dashboards, analysis environments, automated AI/ML workflows, and data pipelines for repeatable analytics.
• Apply engineering discipline to data pipelines and infrastructure to ensure reliability, reproducibility, and trustworthy measurement.
• Work with modern infrastructure tooling and learn new technologies as needed to keep analytic systems secure and smooth.
• Explore open-source small-language model tools to enhance analytic workflows.
• Contribute to research papers, technical writings, and present findings to conferences and senior leaders.

Skills

Statistical modeling

Data science

Communication

Project leadership

Travel readiness

Education

Advanced degree in data science

Tools

R

Python

Linux

Docker

Infrastructure as code

Relational databases

Graph databases

Shiny/Dash

Job description

Carnegie Mellon University’s Software Engineering Institute (SEI) seeks a senior data scientist to lead analytic projects at the intersection of statistics, data engineering, and AI-enabled analytics in support of government and industry missions.

You will build measurement workflows, develop analytic tools (R/Python dashboards), and mentor teams while partnering with domain experts to shape evidence-based decisions for high-impact outcomes.