Research Data Analyst, DIBI

The Defense Industrial Base Institute at Northeastern University (NU) – a rapidly growing defense focused institute that conducts cutting-edge applied R&D – is seeking a highly motivated, experienced and enthusiastic  Jr. Data Researcher with expertise in applying methods/frameworks/systems that apply ML&AI. The Jr. Data Researcher is expected to work as part of a multi-disciplinary team (academia, industry and government) and contribute to the successful execution of federally funded projects/activities.

Responsibilities include providing technical support to Principal investigators or co-principal investigators as a Jr. Data Researcher for a wide range of projects and activities involving machine learning (ML) and artificial intelligence (AI), including autonomy, sensing and communication, and decision support systems, among others. The Jr. Data Researcher will work collaboratively with multi-disciplinary teams across the DIBI Higher Education Consortium, consisting of academic, government, industry partners, to recommend solutions or support institute leadership on prototypes for projects in application areas, including autonomous systems, robotics, and machine learning systems, among others. Specifically, the Jr. Data Researcher will help to create and modify on the back end the existing Navigator methodology; working with other data scientists and leadership across the institute.

Successful candidates will be responsible team players and passionate about machine learning technologies, as well as possess a deep understanding of machine learning technology and experience in turning machine learning systems into practical, state-of-the-art systems that can be enhanced for projects or activities as per federal agency SOW.. A close working relationship with and support of thinking creatively on application of Navigator frame work for government and industry contracts will be required.

The primary office for this position is located at NU’s Boston Campus Through NU, the institute offers an impressive benefits package, including multiple retirement plan options with extremely generous matching, as well as tuition waiver for classes and advanced degree programs. A full description of available benefits can be found on the NU website.

Required

• 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.
  

Preferred

• Master’s degree with a focus 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. 

Desired Skills & Attributes

Required

• Proficiency in Python and familiarity with modern ML/AI development workflows.
• Exposure to C++ and/or Java for performance‑critical components is a plus
• Experience contributing to the design, implementation, testing, or evaluation of ML/AI‑enabled or simulation‑driven software systems.
• 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 database systems, including:
• Relational databases (e.g., PostgreSQL / SQL)
• 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.
• Solid 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 able to 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.

Desired: 

• Exposure to Retrieval‑Augmented Generation (RAG), vector databases, embedding pipelines, or LLM‑enabled systems.
• Familiarity with network science or graph analytics concepts, including:
• Graph modeling and analysis using tools such as NetworkX
• Introductory experience with graph‑based ML or GNNs is a plus
• Monte Carlo or stochastic simulation methods
• Synthetic data generation or simulation‑in‑the‑loop workflows
• Exposure to geospatial data, spatiotemporal datasets, or PostgreSQL/PostGIS is a plus.
• Interest in UI or frontend development for technical or analyst‑facing tools (e.g., Svelte, React, or similar frameworks).
• Familiarity with MLOps concepts, experiment tracking, or reproducible research pipelines.
• Experience working with multidisciplinary teams across research, engineering, and applied R&D environments.

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.  

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.

With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.