Research Data Analyst

Northeastern University is seeking a Research Data Analyst to support federally funded, defense-focused projects that apply machine learning and AI to autonomy, sensing and communication, and decision support systems. The work includes technical support for research efforts tied to the Navigator methodology, with opportunities spanning prototype modeling and simulation, ML tool testing and validation, and contributions to proposal and internal systems build-out.

This onsite role is based in Boston, MA, with an expected annual salary range of USD 60,315 - 85,192. The position requires at least 2 years of relevant experience and is designed for candidates who can prototype, validate, and help scale research deliverables with guidance from senior engineers.

Responsibilities

• Research and Development support to scale the Navigator Methodology for defense contracts (SIB), including development and implementation, prototype modeling and simulation, design, and experimentation (40%).
• Testing and validation of ML tools across sprints, tasks, projects, and deliverables, including recommendations for tools and systems that improve efficiency and support human work (40%).
• Subject matter expertise across application areas and ad hoc sponsor requests, which may involve attending meetings, visits, conferences, and engagements with US Government, industry, and academic partners. Support PI or co-PIs with scoping project budgets as appropriate (systems and tools) (10%).
• Special projects as assigned, collaborating with Managing Director, Founding Director, and other core leadership to scope proposals and opportunities. Partner with Managing Director and Sr. Director, Strategy and Communications to make recommendations for internal systems build-out (10%).

Requirements

• Bachelor’s or Master’s degree in Data science, Computer Engineering, Computer Science, Applied Mathematics, or a closely related field.
• 2–4 years of professional experience in software engineering, data science, or applied R&D, with exposure to machine learning and AI system development in research, prototype, or production environments.
• Proficiency in Python and familiarity with modern ML/AI development workflows.
• Hands-on experience with machine learning frameworks (e.g., PyTorch), including model training, evaluation, and experimentation.
• Familiarity with distributed or accelerated computing environments (e.g., GPU-enabled systems, shared compute clusters).
• Working knowledge of databases, including relational databases (e.g., PostgreSQL/SQL) and exposure to graph databases (e.g., Neo4j, Memgraph, or similar).
• Familiarity with cloud computing environments (e.g., Azure, AWS, or GovCloud equivalents), including containerized or scalable ML workflows.
• Strong software engineering fundamentals, including version control, modular code design, testing, documentation, and reproducibility.
• Ability to rapidly prototype solutions and iterate toward more robust implementations with guidance from senior engineers.
• Self-motivated team member who can work independently on well-defined tasks while contributing to broader project objectives.
• U.S. Citizenship with the ability to obtain and maintain a security clearance.

Technologies

Machine learning (ML), Artificial intelligence (AI), Python, C++, Java, PyTorch, PostgreSQL, SQL, Neo4j, Memgraph, Azure, AWS, GovCloud, GPU-enabled systems, shared compute clusters, cloud computing, containerized, scalable ML workflows, vector databases, Retrieval-Augmented Generation (RAG), embedding pipelines, LLM-enabled systems, NetworkX, graph neural networks (GNNs), Monte Carlo, stochastic simulations, PostGIS, Svelte, React, MLOps, experiment tracking, and reproducible research pipelines.

Preferred Qualifications

• Master’s degree focused on ML/AI, data-intensive systems, network science, optimization, or related areas.
• Experience contributing to government, defense, or security-related R&D programs (internships, fellowships, or full-time roles).
• Familiarity with simulation-based models (e.g., physics-based, network-based, agent-based, or stochastic simulations) for analysis, experimentation, or decision support.

Benefits

• Multiple retirement plan options with extremely generous matching
• Tuition waiver for classes and advanced degree programs
• Medical, vision, and dental
• Paid time off
• Tuition assistance
• Wellness & life
• Retirement, as well as commuting & transportation