About the Opportunity JOB SUMMARY This is a full-time, one-year term appointment with the possibility of renewal. The position is in-person at Northeastern’s Roux Institute in Portland, Maine. The Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University’s Experiential AI Institute, will support the development and delivery of AI and data science solutions across diverse industries. The role is designed for early-career data scientists who will work under the guidance of senior data scientists, AI engineers, and faculty leads. The Data Scientist will contribute to data analysis, feature engineering, model development, evaluation, and documentation, while progressively gaining exposure to production systems, client-facing work, and modern AI practices across Predictive AI and Generative AI use cases.
Education
&
Experience
Master’s degree (required) or Ph.D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field. 0–2 years of industry, research, or applied project experience in data science or machine learning.
Experience
gained through internships, co-ops, academic research, or applied capstone projects is acceptable. Industry experience is preferred. Knowledge, Skills, and Abilities Technical and Analytical Foundations Solid understanding of statistical methods, regression, hypothesis testing, and basic experimental design. Hands-on experience with classical machine learning methods such as linear/logistic regression, decision trees, and gradient boosting. Familiarity with deep learning concepts and modern architectures (e.g., convolutional neural networks or transformers); deep specialization is not required. Exposure to Generative AI concepts and large language models (LLMs) is a plus. Proficiency in Python for data analysis and model development (NumPy, pandas, scikit-learn). Working knowledge of SQL and relational databases. Familiarity with at least one ML or deep learning framework (e.g., PyTorch, TensorFlow, HuggingFace). Model Development and Delivery Support Perform data cleaning, exploratory data analysis (EDA), and feature engineering. Train, evaluate, and compare machine learning models under supervision. Assist with model validation, performance monitoring, and documentation. Contribute to ML pipelines and collaborate with ML engineers on deployment-related tasks. Collaboration and Communication Ability to clearly communicate analytical findings to technical and non-technical audiences with guidance. Collaborate effectively with cross-functional teams including data scientists, engineers, project managers, and faculty experts. Willingness to participate in client meetings in a supporting role. Preferred
Experience
Exposure to NLP, computer vision, or speech processing through coursework or academic/industry projects. Familiarity with cloud platforms (AWS, Azure, or GCP). Understanding of software development best practices such as version control (Git) and Agile workflows. Values & Professional Attributes Ethical and Responsible AI Awareness of ethical AI principles including fairness, transparency, and responsible model use. Willingness to follow established governance, documentation, and review practices. Learning and Growth Mindset Strong curiosity and motivation to learn new tools, techniques, and AI methods. Openness to feedback and mentorship. Execution and Ownership Ability to manage assigned tasks, meet deadlines, and maintain high-quality work. Proactive attitude and willingness to take increasing responsibility over time. Position Type Research Additional 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: 111S Expected Hiring Range: $87,785.00 - $123,998.75 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. Founded in 1898, Northeastern is a global research university and the recognized leader in experiential lifelong learning. Our approach of integrating real-world experience with education, research, and innovation empowers our students, faculty, alumni, and partners to create worldwide impact. Our global university system provides our community and academic, government, and industry partners with unique opportunities to think locally and act globally. The system—which includes 14 campuses across the U.S., U.K., and Canada, 300,000-plus alumni, and 3,000 partners worldwide—serves as a platform for scaling ideas, talent, and solutions. The university’s residential campuses for undergraduate and graduate degrees are located in Boston, London, and Oakland, California. Our research and graduate campuses are in the Massachusetts communities of Burlington and Nahant; Arlington, Virginia; Charlotte, North Carolina; Miami; Portland, Maine; Seattle; Silicon Valley, California; Toronto; and Vancouver. Northeastern’s personalized, experiential undergraduate and graduate programs lead to degrees through the doctorate in 10 colleges and schools across our campuses. Learning emphasizes the intersection of data, technology, and human literacies, uniquely preparing graduates for careers of the future and lives of fulfillment and accomplishment. Our research enterprise, with an R1 Carnegie classification, is solutions oriented and spans the world. Our faculty scholars and students work in teams that cross not just disciplines, but also sectors—aligned around solving today’s highly interconnected global challenges and focused on transformative impact for humankind.