About Software Engineering Institute
Sourced by ZipRecruiter
Company size
1,001 - 5,000 Employees
Headquarters location
Pittsburgh, PA, US
Year founded
1984
Full-time
Posted 18 days ago
Job description
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:
Knowledge, Skills and Abilities:
Desired Experience:
Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
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.
- 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
SalaryMore 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
cmu.edu
Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Scientist?
A: To succeed as a Data Scientist, one must possess core technical skills such as proficiency in programming languages like Python, R, or SQL, as well as expertise in machine learning algorithms, data visualization tools like Tableau or Power BI, and statistical modeling techniques. Additionally, strong soft skills like effective communication, collaboration, and problem-solving abilities, along with traits like curiosity, adaptability, and attention to detail, are crucial for success in this role. By combining these technical and soft skills, Data Scientists can effectively extract insights from complex data, drive business decisions, and drive career growth through continuous learning and innovation.
Q: What is the career path for a Data Scientist?
A: A Data Scientist's typical career progression involves starting as a Junior Data Analyst or Data Scientist, where they develop foundational skills in data analysis, machine learning, and visualization. As they gain experience, they can move into mid-level roles such as Senior Data Scientist or Lead Data Analyst, where they take on more complex projects, mentor junior team members, and contribute to strategic decision-making. Ultimately, senior Data Scientists can transition into leadership positions like Director of Data Science or Chief Data Officer, or pursue specialized roles like Data Engineering or Artificial Intelligence Research Scientist, depending on their interests and skills.
