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Carnegie Mellon University · 22 hours ago

Data Scientist

Pittsburgh, PA

Full-time

Hybrid

Senior Level

5+ years exp

Carnegie Mellon University is seeking a Data Scientist to work at the SEI, utilizing advanced statistics and machine learning to address cybersecurity challenges. The role involves collaborating with clients to develop solutions, conducting research, and presenting findings.

EducationHigher EducationUniversities

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Work with customers to identify areas where advanced statistical techniques can help tackle problems

Plan and develop prototype solutions

Build out final products

Co-author research proposals

Execute studies

Present findings to DoD sponsors and at academic conferences

Craft metrics and experimental designs for large-scale cybersecurity research programs

Develop human-in-the-loop machine learning solutions

Build classifiers to identify security vulnerabilities

Qualification

Predictive modelingStatistical modelingMachine learningData analyticsPythonRNLP / LLMsBig dataInnovative thinkingCommunication

Required

BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) 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 five (5) years of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with two (2) years of experience

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 Defense security clearance

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)