About the Opportunity
JOB SUMMARY
The Defense Industrial Base Institute at Northeastern University (NU) – a rapidly growing defense focused institute that conducts cutting-edge applied R&D – is seeking an experienced and highly capable Jr. Data Scientist with expertise in applying methods/frameworks/systems that apply ML&AI. The Jr. Data Scientist will operate as part of a multi-disciplinary team (academia, industry and government) and will contribute directly to the successful execution of federally funded projects/activities,
Responsibilities include providing technical expertise and analytical support to Principal investigators or co-principal investigators as a Jr. Data Scientist 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 Scientist will work collaboratively with and help guide, multi-disciplinary teams across the DIBI Higher Education Consortium — spanning academic, government, and industry partners — to design, validate, and maintain datasets and analytical products that inform institute leadership and sponsor decision-making. Specifically, the Jr. Data Scientist will take a role in building and maintaining the data pipelines and analytical components underlying the existing Navigator methodology, working closely with — and providing guidance to — data researchers, engineers, 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. A close working relationship with the team, along with creative thinking on the application of the Navigator framework 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.
MINIMUM QUALIFICATIONS
Education & Experience
Required
- Master’s degree in Data Science, Statistics, Computer Science 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 or Ph.D with a focus on data science, 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.
- undefined
Skills & Attributes
Required
- Advanced proficiency in Python and/or R studio and familiarity with modern ML/AI development workflows.
- Exposure to C++ and/or Java for performance‑critical components
- Experience contributing to the design, implementation, testing, or evaluation of ML/AI-enabled or simulation-drive software systems.
- Demonstrated experience with data visualization and reporting tools (e.g., Tableau, Power BI, matplotlib, Plotly), including designing dashboards for executive or sponsor audiences.
- Proven experience independently building, validating, and interpreting statistical or machine learning models, and communicating tradeoffs to non-technical stakeholders.
- Strong command of data cleaning, ETL processes, and data quality assurance practices, including for messy or incomplete real-world datasets.
- Solid software engineering fundamentals, including version control (e.g., Git/GitHub), documentation, and reproducibility.
- Excellent written and verbal communication skills, with experience presenting analytical findings directly to leadership or sponsors.
- 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 cloud computing environments (e.g., Azure, AWS or GovCloud equivalents).
- 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
- Familiarity with 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).
- Exposure to dashboarding or BI tools for analyst-facing or leadership-facing reporting
- Familiarity with MLOps concepts, experiment tracking, or reproducible research pipelines.
- Experience working with multidisciplinary teams across research, engineering, and applied R&D environments.
KEY RESPONSIBILITIES & ACCOUNTABILITIES
Support Research and Development efforts to scale Navigator methodology applied to defense contracts (SIB), to include, development and implementation, prototype modeling & simulation, design, and experimentation. This supports the defense funding received that supports this role (40%)
Test and validation of soAI/ML Tools for sprints, tasks, projects and deliverables; to include scaling of projects by suggesting tools and systems that enhance efficiency and support humans in their work (40%)
Provide subject matter expertise across a diverse set of application areas and ad hoc requests that may come in from the sponsor. Present information and answer questions form government sponsors and stakeholders.Research and support PI or CO-PIs with scoping project budgets as appropriate (Systems, tools) (10%)
Special Projects as assigned: Working closely with Managing Director, Founding Director and other core leadership members, help to scope proposals and opportunities. Working closely with DIBI Leadership Team and Sr. Director, Strategy and Communications to make recommendations on systems build out for internal operations (10%)
Position Type
ResearchAdditional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
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.
Compensation Grade/Pay Type:
110SExpected Hiring Range:
$76,335.00 - $107,823.75With 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.
Skills Required
- Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a closely related field
- 2-4 years of professional experience in software engineering, data science, or applied R&D
- Experience with machine learning and AI system development in research, prototype, or production environments
- Advanced proficiency in Python and/or R Studio and familiarity with modern ML/AI development workflows
- Exposure to C++ and/or Java for performance-critical components
- Experience contributing to the design, implementation, testing, or evaluation of ML/AI-enabled or simulation-driven software systems
- Experience with data visualization and reporting tools such as Tableau, Power BI, Matplotlib, or Plotly, including executive or sponsor dashboards
- Experience independently building, validating, and interpreting statistical or machine learning models
- Experience communicating analytical tradeoffs to non-technical stakeholders
- Experience with data cleaning, ETL processes, and data quality assurance for messy or incomplete datasets
- Software engineering fundamentals including version control, documentation, and reproducibility
- Excellent written and verbal communication skills, including presenting analytical findings to leadership or sponsors
- U.S. citizenship with the ability to obtain and maintain a security clearance
- Master's degree or Ph.D. focused on data science, data-intensive systems, network science, optimization, or related areas
- Experience contributing to government, defense, or security-related R&D programs
- Familiarity with simulation-based models, including physics-based, network-based, agent-based, or stochastic simulations
- Exposure to Retrieval-Augmented Generation, vector databases, embedding pipelines, or LLM-enabled systems
- Familiarity with Azure, AWS, or GovCloud computing environments
- Introductory experience with graph-based machine learning or graph neural networks
- Monte Carlo or stochastic simulation experience
- Synthetic data generation or simulation-in-the-loop workflow experience
- Familiarity with geospatial or spatiotemporal data, PostgreSQL, or PostGIS
- Interest in UI or frontend development using Svelte, React, or similar frameworks
- Experience with dashboarding or business intelligence tools
- Familiarity with MLOps, experiment tracking, or reproducible research pipelines
- Experience working with multidisciplinary research, engineering, and applied R&D teams
Northeastern University Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Northeastern University and has not been reviewed or approved by Northeastern University.
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Leave & Time Off Breadth — Paid time off is described as extensive, including 22–26 vacation days, 12 sick days, 13 holidays, and paid parental leave for birth/adoption. Additional paid leave is also outlined, including up to 26 weeks of paid medical leave and up to 12 weeks of paid family leave for eligible employees.
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Retirement Support — Retirement support is positioned as a standout, with an employer contribution described as 10% when an employee contributes 5%, alongside immediate vesting once eligible. This is presented as unusually generous relative to typical employer retirement offerings.
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Parental & Family Support — Family-oriented benefits are emphasized through tuition assistance for employees and dependents and access to backup childcare and family-care resources. Tuition remission/discount structures are highlighted as a major value driver, especially for employees with children and for long-tenured staff.
Northeastern University Insights
What We Do
Founded in 1898, Northeastern is a global research university with a distinctive, experience-driven approach to education and discovery. The university is a leader in experiential learning, powered by the world’s most far-reaching cooperative education program. We integrate classroom study with opportunities for professional work, research, service, and global learning in more than 100 countries. The same spirit of collaboration guides a use-inspired research enterprise focused on solving global challenges in health, security, and sustainability. Northeastern offers a comprehensive array of undergraduate and graduate programs leading to degrees through the doctorate in nine colleges and schools, and select graduate programs at campuses in Boston, Charlotte, N.C., San Francisco Bay Area, Seattle, and Toronto. Campuses in Burlington, MA, and Nahant, MA, are home to research institutes for homeland security and coastal sustainability, respectively








