Senior Data Scientist

Jobtailor; Pennsylvania; On-site; USD 110,000 - 165,000; Full time

Job summary

Jobtailor is seeking a highly qualified data science and ML research professional to advance cybersecurity research for government and industry clients. The role emphasizes developing prototype solutions, rigorous experimental design, and collaboration across academics and sponsors.

Ideal candidates have deep expertise in predictive modeling, AI/ML, NLP, LLMs, and related modern frameworks, with strong communication and cross-disciplinary collaboration skills.

Qualifications

• 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
• MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience
• PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with five (5) years of experience
• Willing to complete modest travel to various locations to support the SEI’s overall mission
• Subject to 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)
• 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), 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), working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)

Responsibilities

• Use advanced statistics, data analytics, machine learning, and artificial intelligence to help government and industry clients research and solve cybersecurity challenges
• Work with customers to identify areas where advanced statistical techniques can help tackle problems
• Plan and develop prototype solutions and build out final products
• Co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences
• Engage in research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems
• 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

Skills

Advanced statistics

Data analytics

Machine learning

Artificial intelligence

Statistical modeling

R/Python/MATLAB

Communication

Big data

Time-series forecasting

NLP/LLMs

Prompt engineering

Causal inference

Education

BS in quantitative field

MS in quantitative field

PhD in quantitative field

Tools

R

Python (numpy/scipy/pandas/polars)

MATLAB

Spark

Trino

Snowflake

BigQuery

Databricks

LightGBM

XGBoost

CatBoost

PyTorch

TensorFlow

LangChain

LlamaIndex

Haystack

Job description

Responsibilities

• Use advanced statistics, data analytics, machine learning, and artificial intelligence to help government and industry clients research and solve cybersecurity challenges
• Work with customers to identify areas where advanced statistical techniques can help tackle problems
• Plan and develop prototype solutions and build out final products
• Co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences
• Engage in research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems
• 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

Qualifications

• 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
• MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience
• PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with five (5) years of experience
• Willing to complete modest travel to various locations to support the SEI’s overall mission
• Subject to 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)
• 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), 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), working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)

Core Competencies

Demonstrates expertise in advanced statistics, data analytics, and machine learning to address cybersecurity challenges, with a strong foundation in statistical modeling and programming. Capable of developing innovative solutions and presenting findings to diverse audiences.