Associate Data Scientist
Software Engineering Institute | Carnegie Mellon University
About the role
What We Do:
Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity challenges. In this role, you will work with our customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products. You'll get a chance to work with elite cybersecurity professionals and university faculty to build new technologies that will influence national cybersecurity strategy for decades to come. You will co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences.
Our team works on a wide range of projects. Our current work includes research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and experimental designs for large-scale cybersecurity research programs, develop human-in-the-loop machine learning solutions, and build classifiers to identify security vulnerabilities. If you are a data science or statistics expert with an interest in cybersecurity, we want to hear from you!
Requirements:
BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with one (1) year of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline.
Willingness to complete modest travel to various locations to support the SEI’s overall mission.
You will be subject to a background check and must be able obtain and maintain a U.S. Department of War security clearance.
Knowledge, Skills and Abilities:
Experience in predictive modeling, data science, and/or AI & machine learning
Deep understanding of statistical modeling techniques and advanced data analytics
Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy/scipy/pandas/polars, MATLAB, etc.)
Innovative and inquisitive with ability to imagine novel analytical solutions to problems Thrives in a multi-disciplinary environment
Strong communication skills
Expertise in one or more of the following:
Recommendation systems
Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.)
NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering)
Causal inference / uplift modeling / synthetic controls
Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow)
LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Experience deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar)
Experience working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)
Desired Experience:
Experience in cybersecurity and privacy is a plus is a plus
Experience in U.S. Government work and/or with FFRDCs, UARCs an National Labs is a plus
Demonstrated ability to learn new concepts and grow into new areas of work
Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff – Regular
Full time/Part time
Full time
Pay Basis
Salary
More Information:
Please visit “Why Carnegie Mellon” to learn more about becoming part of an institution inspiring innovations that change the world.
Click here to view a listing of employee benefits
Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
Statement of Assurance
Responsibilities
- Identify cybersecurity problems that can benefit from advanced statistical techniques and develop prototype solutions and final products.
- Conduct research in AI, machine learning, data analytics, and cybersecurity.
- Co-author research proposals, execute studies, and present findings to sponsors and at academic conferences.
Qualifications
- Bachelor’s degree in a quantitative discipline and 3 years of experience, master’s degree and 1 year of experience, or PhD.
- Experience in predictive modeling, data science, or AI and machine learning, with strong statistical modeling and data analytics skills.
- Proficiency with a mathematical or statistical programming package such as Python, R, or MATLAB.
- Expertise in at least one relevant area such as recommendation systems, forecasting, NLP/LLMs, causal inference, modern ML frameworks, model deployment, or big data.
- Strong communication skills and ability to work in a multidisciplinary environment.
- Willingness to travel modestly and ability to obtain and maintain a U.S. Department of War security clearance.
Skills mentioned
About Software Engineering Institute | Carnegie Mellon University
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. We have been working with the DoW, government agencies, and private industry since 1984 to help meet mission goals and gain strategic advantage.