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 Northeasterns Roux Institute in Portland Maine.

The Data Scientist at the AI Solutions Hub (AISH) the delivery arm of Northeastern Universitys 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

• Masters degree (required) or Ph.D. (optional) in Computer Science Engineering Applied Mathematics Statistics or a closely related field.

• 02 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

Additional Information

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.

Compensation Grade/Pay Type:

Expected Hiring Range:

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.