Senior Data Scientist

Carnegie Mellon University

Senior Data Scientist utilizing advanced analytics and AI to tackle cybersecurity challenges. Collaborating with elite professionals to influence national cybersecurity strategy over time.

Posted 7/18/2026full-timePittsburgh • Pennsylvania, Virginia • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced statistical modeling, machine learning, and data analytics to develop innovative solutions for cybersecurity challenges. Proficient in deploying models and working with big data technologies to influence national cybersecurity strategy.

Highest-signal resume keywords

Predictive ModelingStatistical Modeling TechniquesMachine Learning FrameworksBig Data TechnologiesStrong Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningAdvanced Data AnalyticsStatistical Programming (R, Python)Recommendation SystemsTime-Series ForecastingNatural Language ProcessingCausal InferenceModel DeploymentBig Data Processing

Soft Skills

Innovative ThinkingInquisitive NatureCollaboration in Multi-Disciplinary Environments

Tools & Technologies

LightGBMXGBoostCatBoostPyTorchTensorFlowFastAPISageMakerBigQueryDatabricksSnowflake

Industry Keywords

CybersecurityArtificial IntelligenceGenerative AILarge Language ModelsComputer VisionHuman-in-the-Loop Machine LearningSecurity Vulnerabilities

Tech Stack

Tools & technologies

BigQueryCyber SecurityNumpyPandasPythonPyTorchSparkTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with ten (10) 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 eight (8) years of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with five (5) 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 War 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).

Benefits

Comp & perks

Please visit “ Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world.
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