DATA SCIENTIST (CYBER/CLOUD)
Quantum Research Int is seeking a motivated Mid-Level (or Junior)
Data Scientist to support advanced AI/ML and large language model (LLM) initiatives within a cybersecurity and risk analysis platform. You will contribute to the development, deployment, and integration of predictive models and LLM-based solutions to process structured and unstructured data (including SBOMs, CVEs, vulnerability data, and critical program information), generate actionable insights, and support data-informed decision making in a high-stakes defense environment.
Responsibilities: - Support the formulation, design, and execution of data-driven projects focused on cybersecurity risk prioritization, vulnerability analysis, exposure trends, anomaly detection, and automated risk reporting.
- Develop, fine-tune, and assist in deploying AI/ML models and LLM-based solutions (e.g., for natural language understanding, summarization, and insight generation from unstructured sources such as SBOMs and technical documentation).
- Help integrate model outputs into data pipelines, dashboards, and visualization tools to deliver clear insights for technical and non-technical stakeholders.
- Collaborate with data analysts, software developers, and cross-functional teams to embed predictive analytics and LLM capabilities into existing platforms.
- Clean, collate, and preprocess complex datasets from multiple sources; assess and improve data quality.
- Apply statistical methods, machine learning algorithms, and LLM techniques to extract actionable insights under guidance.
- Perform model validation, performance monitoring, and testing.
- Optimize models for accuracy, scalability, and usability.
- Produce and present reports, summaries, and visualizations that communicate findings and implications.
- Stay current with advancements in AI/ML, LLMs, and cybersecurity data domains.
- Contribute to MLOps practices including model versioning and deployment support.
- Assist in LLM-driven techniques for assessing compromised datasets to gauge impact and score risk.
Requirements:- 2-5+ years of professional experience as a Data Scientist with emphasis on AI/ML model development and deployment (0-3 years for Junior level).
- Bachelor's degree required; Master's preferred in Data Science, Computer Science, Statistics, Mathematics, or a closely related field.
- Proficiency in Python (primary); experience with R is a plus.
- Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and basic LLM implementation/fine-tuning (BERT, GPT-style models, LLaMA/Ollama, or equivalents).
- Strong proficiency in data manipulation and analysis (Pandas, NumPy) and SQL.
- Ability to translate technical outputs into clear, actionable insights and presentations.
- Familiarity with cybersecurity data types and concepts (CVEs, SBOMs, vulnerability severity scoring, risk exposure metrics) or enterprise risk management domains is beneficial.
- Active TS//SCI security clearance (or ability to obtain and maintain).
- Preferred certs: CISSP, CySA+, Security+, CEH
Desired/Preferred Skills:- Prior experience in cybersecurity, defense, national security, or enterprise risk management environments.
- Experience integrating AI/ML or LLM solutions with cloud platforms (AWS SageMaker, Azure ML, GCP) or on-premises systems.
- Knowledge of basic MLOps tools and practices.
- Experience with business intelligence and dashboard tools (Tableau, Power BI).
- Familiarity with big data frameworks or large-scale data processing.
- Additional programming skills (Java, C++) are a plus.
- Strong foundation in statistics, linear algebra, and experimental design.
- This role combines technical AI/ML and LLM contributions with collaboration in a sensitive, cleared environment. Ideal candidates are proactive, eager to learn, and comfortable applying advanced modeling to real-world cybersecurity challenges.
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