Principal Engineer - Data Science

The Principal Engineer Data science combine a high level of technical expertise with sound business acumen and a good understanding of engineering processes. Principal Engineers are part of a formal career path for technical personnel wanting to continue to develop and grow their technical competencies while having increasingly more impact on the business.
As recognized experts in specialized fields, they normally lead or support projects and initiatives with broad scope and high impact to the business. They are responsible for major and complex assignments with long-term business implications. This role contributes to the overall strategy and manages complex issues within functional area of expertise.

Main Responsibilities

Technical Leadership

• Support Consulting Engineers in business line technology strategy definition and Multi-Generational Product Plan (MGPP).
• Chair Design reviews for individual components, sub-assemblies and key engineering deliverables at tendering and contract execution stages. Support Consulting Engineers in governance and trainings to reinforce proper execution of design review guidelines.
• Identify, develop, evaluate, and introduce engineering solutions to create market winning proposals in anticipation of business product needs. Provide key technical direction to large projects during contract execution phase.
• Provide technical consultation on product problems throughout the business including supplier and field support and perform technical rescues when needed.
• Participate Patent Evaluation Board (PEB) to protect technology that gives the business a competitive advantage, as well as protecting the intellectual property rights of the company.
• Represent the business externally at conferences or in professional working bodies (IEC, CIGRE etc) and maintain active relationship with relevant academic institutions to promote research projects and other academic cooperations.
• Lead early research and proof-of-concepts for promising technology applications.
• Provide ad-hoc technical guidance to the Engineering/Technology leadership team as required, e.g., joining customer negotiations or supplier audits.

Engineering/Technology Practices

• Support Consulting Engineers to safeguard design qualities. Organize lessons-learnt in ones own domain and make sure they are well documented and communicated throughout the organization to prevent repeated mistakes.
• Maintain an active role in product introduction, cost improvements, schedule adherence and problem resolution to meet business needs.
• Provide technical consultation to cross-functional teams within the business to improve or resolve manufacturing, supply, or field issues.

Competency Governance

• Develop technical competencies by establishing and delivering structured technical training schemes within ones own business lines.
• Support Consulting Engineers in reviewing Engineering competency frameworks specific to ones own business line.

People Development

• Actively support Consulting Engineers with staff development & succession planning.
• Participate interviews for promotions or hirings within Engineering/Technology up to the level of Senior Engineer.
• Actively mentor and coach identified high potential Engineering talents within ones business lines.

Additional Information

Qualifications & Requirements

Master of Science in Computer Science, Machine Learning, Engineering, or Mathematics.

At least 10 years of experience in an engineering or data science capacity

Desired Characteristics

• Experience with state-of-the-art machine learning technologies & techniques in at least one of those domains: Natural Language Processing, Time Series, Computer Vision
• Ability to work across organizations in a matrix environment
• Preferably having taken a Senior Engineer or Senior Researcher role
• Strong oral and written communication skills
• Strong interpersonal and leadership skills
• Problem analysis and resolution skills
• Able to pursue Engineering integrity in adverse conditions
• Able to interface effectively with most levels of the organization
• Lean experience preferred