Principal Engineer – Data Science

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.

Responsibilities

• 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.
• 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.
• Support Consulting Engineers to safeguard design qualities. Organize lessons-learnt in one’s 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.
• Develop technical competencies by establishing and delivering structured technical training schemes within one’s own business lines.
• Support Consulting Engineers in reviewing Engineering competency frameworks specific to one’s own business line.
• 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 one’s business lines.

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.

Relocation Assistance Provided

No. This is a remote position.