Associate Data Scientist
Software Engineering Institute | Carnegie Mellon University
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. Current Projects 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. 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. Subject to a background check and must be able to 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). Deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar). Working with big data (Spark, Trino, Snowflake, BigQuery, Databricks). Desired Experience Experience in cybersecurity and privacy is a plus. Experience in U.S. Government work and/or with FFRDCs, UARCs and 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 Equal Opportunity Employer Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran. Statement of Assurance. #J-18808-Ljbffr Software Engineering Institute | Carnegie Mellon University
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