Manager - Data Science

Role Description

As a Manager - Data Science, you will lead an international team consisting of data scientists and machine learning practitioners responsible for:

• Developing, experimenting with, deploying, and benchmarking AI/ML models.
• Working on prompt-engineered solutions embedded into Westinghouse digital products.
• Collaborating with Westinghouse leaders to understand business and product needs.
• Supporting themes such as Asset Management, Work Management, and Business Process Optimization.
• Identifying critical skill needs and addressing gaps to ensure necessary capabilities in classical ML, deep learning, and generative AI.

You will report to the Director, AI Data Infrastructure and work remotely.

Qualifications

• A data science, machine learning, or applied AI management background leading international team members.
• Familiarity with the nuclear and energy industries.
• Experience with model development, experimentation frameworks, MLOps practices, and 3rd party AI/ML platforms and foundation models.
• B.S. degree in business management, computer science, data science, industrial engineering, statistics or equivalent.
• 10+ years of experience in business, operations or consultation services with progression and complexity.
• Microsoft Certified: Azure Data Engineer Associate helpful.
• Microsoft Certified: Azure Database Administrator Associate helpful.

Requirements

• Engage with the Digital and Innovation (D&I) leaders to promote the D&I vision.
• Provide input and accomplish the digital roadmap to improve safety, profitable growth, and process efficiency.
• Assume responsibility for the success of model development, experimentation, deployment, quality assurance, and prompt engineering practices.
• Lead the data science team in developing, evaluating, and deploying AI/ML models and generative AI solutions.
• Ensure models are production-ready, benchmarked against clear performance criteria, and embedded into digital solutions.
• Train team members responsible for model deployment and monitoring in production.
• Establish best practices for experimentation, model validation, reproducibility, versioning, and responsible AI.

Benefits

• Comprehensive Medical benefits including medical, dental, vision, prescription coverage, and Health Savings Account (HSA) with employer contributions options.
• Wellness Programs designed to support employees in maintaining their health and well-being.
• 401(k) with Company Match Contributions to support employees' retirement.
• Paid Vacations and Company Holidays.
• Opportunities for Flexible Work Arrangements to promote work-life balance.
• Educational Reimbursement and Comprehensive Career Programs to help employees grow in their careers.
• Global Recognition and Service Programs to celebrate employee accomplishments and service.
• Employee Referral Program.