R&D Engineer Algorithm & Data

Description

• Build health indexes, failure mode models, and prescriptive maintenance actions.
• Analyse time-series and condition-monitoring data (DGA, thermal, load, etc.).
• Keep up with industry standards advancements in analytics for asset condition monitoring
• Evaluate algorithm performance for continuos improvement
• Develop and validate algorithms for the automated assessment of asset health, for failure mode identification and for condition-based maintenance.
• Translate expert domain knowledge into structured logic and models.

Requirements

• Experience in data modelling, feature engineering, and performance evaluation techniques.
• Strong programming skills in Python (pandas, numpy, scikit-learn).
• Ability to work through R&D ambiguity and iterate toward incremental product value.
• Background in condition monitoring and predictive maintenance or reliability engineering.
• A blend of data science and engineering skills.
• Hands-on expertise in modelling and simulation, including physical models and digital twins for electric grid assets.
• Bachelors or Masters degree in Computer Engineering, Electrical Engineering, Physics, Applied Physics, Data Science or related field.
• hands on experience in designing, deploying and maintaining rule-based expert systems
• Curious mindset, willingness to deeply understand how assets work
• Hands-on expertise in DSP, time series analysis and modelling

Benefits

• Subsidised Gym Membership
• Hybrid Working
• Company Pension & Life Assurance Schemes
• Competitive salary
• On-site parking

Training + Development

Interview process

Visa Sponsorship

Security clearance