Probabilistic Modeling Specialist

Description

• In a partner ecosystem, you collaborate with universities, research institutes, and other industrial players and engage in joint research projects
• You predict component reliability and develop novel modeling techniques to optimize product design and service concepts and you ensure that your tools and methods are broadly applicable across various areas of the business
• Working within our distributed team, you will serve as a Subject Matter expert dedicated to developing advanced probabilistic solutions for applications along the value-chain
• You support the Product Owners in delivering projects and document and share methods, processes, and project results. You regularly communicate and present your findings
• You support and coach the business in the application and implementation of new methods for probabilistic analysis, machine learning, and optimization.
• You keep up to date with the latest developments in physics-based modelling, advanced statistics, and data science principles and theories to support the business in making truly data-driven decisions

Requirements

• You have excellent writing and communication skills in English, knowledge of any other language is a plus
• Applicants must be legally authorized for employment in the United States without need for current or future employer-sponsored work authorization. Siemens Energy employees with current visa sponsorship may be eligible for internal transfers.
• You are a great teammate with a strong customer focus, you like to work in multi-disciplinary teams, and you navigate easily in a global & multicultural environment with a will to learn and constantly improve own skills.
• Excellent analytical skills and expertise in statistical modeling (e.g. uncertainty quantification, failure and reliability analysis, maximum likelihood estimation) combined with strong programming skills (e.g. Python, C/C++, R) to develop both data-driven and physics-based models
• Advanced/Masters degree in one of the following fields: Computer science, mathematics, physics, engineering. A PhD is considered a plus.
• 2+ years hands-on experience in the field of numerical simulations, data science, or machine learning, preferably in an industry-related environment (ideally within the energy sector). Background may include domains such as material science, fatigue/fracture, degradation and life modeling of components/systems, non-destructive testing, finite-element simulation, molecular dynamics, CFD, design optimization, and efficiency modeling.

Benefits

• Family building benefits
• 401K savings plan with company match
• Parental leave
• Career growth and development opportunities
• Supportive work culture
• Company paid Health and wellness benefits
• Paid Time Off and paid holidays

Training + Development

Interview process

Visa Sponsorship

Security clearance