Sr. Data Scientist

About the Opportunity

1. Job Summary

This is a full-time one-year term appointment with the possibility of renewal.

The Senior Data Scientist at the AI Solutions Hub (AISH) the delivery arm of Northeastern Universitys Experiential AI Institute will lead the development and delivery of AI solutions across diverse industries. The role involves building end-to-end AI pipelinesfrom business problem scoping to deployment and monitoring of production-grade modelswith a focus on both Generative AI and Deep Learning.

The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and brings a strong combination of academic and industry experience. They will possess deep hands-on expertise in modern AI architectures including convolutional neural networks transformers and diffusion models. The role also requires significant experience in classical machine learning methods such as decision trees gradient boosting machines and both shallow and deep learning networks. A demonstrated ability to interface with clients to gather requirements communicate insights and lead solution design are essential. A successful candidate will also demonstrate mentoring experience and a strong track record of translating complex business needs into scalable AI solutions. Experience in the consulting industry is preferred.

2. Education & Experience

Ph.D. (strongly preferred) or Masters degree in Computer Science Engineering Applied Mathematics Statistics or a closely related field with a focus on Deep Learning or Generative AI.

Minimum of 5 years of industry experience in designing developing and deploying AI / ML solutions across sectors including hands-on model building.

Demonstrated academic and industrial contributions in Generative AI and Deep Learning including practical deployment of models using modern architectures such as convolutional neural networks transformers and diffusion models.

Proven experience building AI solutions using classical ML algorithms such as decision trees gradient boosting machines and shallow neural networks.

Demonstrated client-facing experience including engagement scoping expectation management and delivery leadership.

Strong ability to translate complex technical findings into business insights for both technical and non-technical audiences.

Track record of cross-functional collaboration and stakeholder engagement.

Experience in commercializing AI technologies including data-driven tools and platforms.

3. Knowledge Skills and Abilities

Technical and Analytical Expertise

Advanced understanding of statistical methods regression hypothesis testing and experimental design.

Deep expertise in predictive modeling classical ML algorithms (e.g. decision trees gradient boosting) large language models (LLMs) generative AI MLOps and AutoML using frameworks like PyTorch TensorFlow HuggingFace and LangChain.

Demonstrated experience with modern AI model architectures including convolutional neural networks transformers and diffusion models.

Demonstrated experience deploying ML systems into production environments with a focus on performance robustness and scalability.

Domain expertise in NLP computer vision or speech processing.

Proficient in Python for software and ML pipeline development.

Experience with SQL NoSQL and cloud platforms (AWS Azure GCP).

Familiar with distributed data systems (e.g. Apache Spark) and workflow orchestration tools (e.g. Airflow Prefect).

Solid background in software development including Linux Git and OOP languages such as Python Java or C.

Project and Delivery Management

Strong grasp of Agile / Scrum development practices.

Proven industry experience in requirements gathering and scoping solutions.

The ability to convert high-level business problems into actionable project plans and deliverables.

Client and Stakeholder Engagement

Excellent interpersonal and communication skills to work directly with clients.

Proven ability to develop custom AI strategies aligned with client goals.

4. Preferred Experience

Hands-on experience with distributed data processing (e.g. Apache Spark Hadoop).

Track record of building and scaling ML pipelines for both structured and unstructured data.

Proven record of technical leadership in architecture and delivery of robust and scalable AI systems.

At least 3 years of MLOps experience including deployment and monitoring of AI models.

Proven experience scaling GenAI models (e.g. LLMs diffusion models) in production settings.

Familiarity with containerization (Docker) and orchestration tools (Kubernetes).

Preferred experience with MLOps tools and frameworks such as MLFlow Airflow Prefect and related model monitoring and lifecycle management platforms.

Demonstrated experience collaborating with clients to deliver tailored AI solutions that solve high-value problems.

5. Values & Abilities

Leadership and Mentorship

Commitment to mentoring junior staff fostering a culture of technical excellence and growth.

Ethical and Responsible AI Advocacy :

Adheres to principles of ethical AI ensuring transparency fairness and accountability in all solutions.

Collaboration and Communication :

Strong communicator capable of bridging the gap between technical and non-technical audiences.

Team-oriented open to feedback and committed to inclusive cross-disciplinary collaboration.

Continuous Learning and Technical Curiosity

Passion for continuous improvement and staying up to date on cutting-edge AI research and tools.

Execution Excellence :

Demonstrated ability to manage multiple priorities under tight deadlines while maintaining high quality.

Proactive and solutions-driven with strong ownership of project outcomes.

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 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 :

113S

Expected Hiring Range :

$112180.00 - $162662.50

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.

Required Experience :

Senior IC

Key Skills

Laboratory Experience,Immunoassays,Machine Learning,Biochemistry,Assays,Research Experience,Spectroscopy,Research & Development,cGMP,Cell Culture,Molecular Biology,Data Analysis Skills

Employment Type : Full-Time

Experience : years

Vacancy : 1

Monthly Salary Salary : 112180 - 162662