Lead data-driven innovation at Everllence, transforming complex engineering datasets into actionable insights for sustainable propulsion systems. Develop ML models, virtual sensors, and decision-support tools to optimize emissions, fuel efficiency, and system reliability. Collaborate with cross-functional teams to advance AI/ML integration in marine two-stroke engines and alternative fuel technologies.
Key Highlights
Develop and deploy ML models, virtual sensors, and optimization algorithms for engine control systems and emissions reduction
Collaborate with R&D engineers, specialists, and operators to translate data into trusted engineering decisions
Establish robust data quality frameworks and model validation processes for safety-critical applications
Key Responsibilities
Transform operational, simulation, and test data into actionable insights for engine control systems and emissions technologies
Develop and validate ML models, virtual sensors, and optimization algorithms for real-world engineering challenges
Collaborate with R&D engineers and technical specialists to ensure data-driven solutions align with safety-critical requirements
Establish and enforce data quality standards and model validation protocols for high-confidence outputs
Support initiatives in alternative fuels, diagnostics, simulation, and future digital products for marine propulsion
Technical Skills Required
Machine Learning
Data Science
Python
Benefits & Perks
Flexible working hours and remote work options
Relocation support package (CPR registration, tax, work permits)
Work-life balance, social clubs, and well-being initiatives
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Nice to Have
Experience applying data science in engineering environments
Knowledge of edge ML and LLM integration
Familiarity with uncertainty assessment and risk communication for technical audiences
Job Description
R&D Data ScientistJob-ID: 14225Location:København SV, Danish Capital Reg., DK, 2450Country: DKDo you enjoy turning complex data into actionable insights? Are you excited by applying data science and AI to support the green transition? If you’re passionate about using data to solve real engineering challenges and working with purpose, we’d love to hear from you.
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