R&D Engineer - Algorithm & Data
Role details
Job location
Tech stack
Job description
We are looking for an R&D Engineer to join our R&D and discovery team. You will design the next generation of algorithms that assess power assets' health, predict failures, and recommend prescriptive actions for utilities.
This role sits at the intersection of engineering, data science, and applied research. You will work closely with domain experts to translate knowledge of electric grid assets operations and diagnostics into algorithms that produce health indexes, risk assessments, and diagnostics.
If you enjoy diving into how electric grid assets work and transforming that understanding into actionable insights, this role is for you.
What You'll Do
- 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.
- Build health indexes, failure mode models, and prescriptive maintenance actions.
- Analyse time-series and condition-monitoring data (DGA, thermal, load, etc.).
- Evaluate algorithm performance for continuos improvement
- Keep up with industry standards advancements in analytics for asset condition monitoring
Requirements
Do you have experience in Python?, Do you have a Master's degree?, * Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Physics, Applied Physics, Data Science or related field.
- Strong programming skills in Python (pandas, numpy, scikit-learn).
- Hands-on expertise in DSP, time series analysis and modelling
- Experience in data modelling, feature engineering, and performance evaluation techniques.
- A blend of data science and engineering skills.
- Ability to work through R&D ambiguity and iterate toward incremental product value.
- Curious mindset, willingness to deeply understand how assets work
Nice to have
- Hands-on expertise in modelling and simulation, including physical models and digital twins for electric grid assets.
- hands on experience in designing, deploying and maintaining rule-based expert systems
- Background in condition monitoring and predictive maintenance or reliability engineering.
Benefits & conditions
- Competitive salary
- Company Pension & Life Assurance Schemes
- On-site parking
- Hybrid Working
- Subsidised Gym Membership
Our Values
- We work together
- We believe in people
- We won't accept the 'way it has always been done'
- We listen to learn
- We're trying to do the right thing
