Northeastern University
About the Opportunity
This is a full‑time one‑year term appointment with the possibility of renewal. Job Summary
The Senior Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University’s Experiential AI Institute, will lead the development and delivery of AI solutions across diverse industries. The role involves building end‑to‑end AI pipelines from business problem scoping to deployment and monitoring of production‑grade models with a focus on both Generative AI and Deep Learning. Education & Experience
Ph.D. (strongly preferred) or Master’s 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 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: 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. Knowledge, Skills, and Abilities
Technical and Analytical Expertise Advanced understanding of statistical methods, regression, hypothesis testing, and experimental design. Deep expertise in predictive modeling and large language models (LLMs), generative AI, MLOps, and AutoML using frameworks such as PyTorch, TensorFlow, HuggingFace, and LangChain. Experience with modern AI model architectures including convolutional neural networks, transformers, and diffusion models. Deployment of ML systems into production with a focus on performance, robustness, and scalability. Domain expertise in NLP, computer vision, or speech processing. Proficient in Python, 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: Linux, Git, and OOP languages such as Python, Java, or C. Project and Delivery Management Strong grasp of Agile/Scrum development practices. Proven experience in requirements gathering and scoping solutions. 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. Preferred Experience
Hands‑on experience with distributed data processing (e.g., Apache Spark, Hadoop). Track record of building and scaling ML pipelines for 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. Experience scaling GenAI models (e.g., LLMs, diffusion models) in production settings. Familiarity with containerization (Docker) and orchestration tools (Kubernetes). Experience with MLOps tools and frameworks such as MLFlow, Airflow, Prefect, and related model monitoring platforms. Demonstrated collaboration with clients to deliver tailored AI solutions that solve high‑value problems. Values & Abilities
Leadership and Mentorship Commitment to mentoring junior staff and fostering a culture of technical excellence and growth. Ethical and Responsible AI Advocacy Adherence to ethical AI principles 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. 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, including medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement, and commuting & transportation. 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:
$112,180.00 – $162,662.50 Salary ranges are reviewed regularly and are subject to change. Required Experience
Senior IC Employment Type
Full‑Time Vacancy
1
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This is a full‑time one‑year term appointment with the possibility of renewal. Job Summary
The Senior Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University’s Experiential AI Institute, will lead the development and delivery of AI solutions across diverse industries. The role involves building end‑to‑end AI pipelines from business problem scoping to deployment and monitoring of production‑grade models with a focus on both Generative AI and Deep Learning. Education & Experience
Ph.D. (strongly preferred) or Master’s 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 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: 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. Knowledge, Skills, and Abilities
Technical and Analytical Expertise Advanced understanding of statistical methods, regression, hypothesis testing, and experimental design. Deep expertise in predictive modeling and large language models (LLMs), generative AI, MLOps, and AutoML using frameworks such as PyTorch, TensorFlow, HuggingFace, and LangChain. Experience with modern AI model architectures including convolutional neural networks, transformers, and diffusion models. Deployment of ML systems into production with a focus on performance, robustness, and scalability. Domain expertise in NLP, computer vision, or speech processing. Proficient in Python, 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: Linux, Git, and OOP languages such as Python, Java, or C. Project and Delivery Management Strong grasp of Agile/Scrum development practices. Proven experience in requirements gathering and scoping solutions. 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. Preferred Experience
Hands‑on experience with distributed data processing (e.g., Apache Spark, Hadoop). Track record of building and scaling ML pipelines for 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. Experience scaling GenAI models (e.g., LLMs, diffusion models) in production settings. Familiarity with containerization (Docker) and orchestration tools (Kubernetes). Experience with MLOps tools and frameworks such as MLFlow, Airflow, Prefect, and related model monitoring platforms. Demonstrated collaboration with clients to deliver tailored AI solutions that solve high‑value problems. Values & Abilities
Leadership and Mentorship Commitment to mentoring junior staff and fostering a culture of technical excellence and growth. Ethical and Responsible AI Advocacy Adherence to ethical AI principles 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. 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, including medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement, and commuting & transportation. 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:
$112,180.00 – $162,662.50 Salary ranges are reviewed regularly and are subject to change. Required Experience
Senior IC Employment Type
Full‑Time Vacancy
1
#J-18808-Ljbffr