Role overview
Ecotricity, the UK’s first true green energy provider, has a strong internal team supporting and developing solutions across multiple mission critical platforms including Databricks and Salesforce. This technical hands-on role, of Data Scientist, will contribute to our delivery of projects, BAU, and helping Ecotricity become more efficient by leveraging our data.
The Ecotricity Technology department is a small friendly team with a strong focus on getting results, with everyone committed to delivering both individually and as part of the group/project.
We’re proud to be an ethical company, and this naturally attracts ethical people, making for a good safe working environment and a team that works and wins together. We also have a competitive benefits package and chose to invest in our people whenever we can.
Responsibilities
- Take ownership of designing, building, validating, and maintaining data science solutions, from exploratory analysis through to production deployment.
- Build strong relationships with key stakeholders outside the department.
- Be accountable for the quality, robustness, and reproducibility of analytical outputs, ensuring issues in data, assumptions, or model performance are identified and addressed promptly.
- Promote and contribute to best practice in data science, including experimentation, model validation, version control, and ethical use of data.
- Overall responsibility for ensuring that faults are resolved swiftly, and background processes are robust and actively monitored.
- Seek day to day opportunities to upskill and cross train with your peers.
Benefits
- Canteen
- Casual dress
- Free parking
- On-site parking
- Ecotricity offers hybrid working. Are you able to reliably commute to our Stroud office 2/3 days per week?
- Will you now or in the future require sponsorship for employment visa status?
- United Kingdom (preferred)
About the company
- Strong grounding in statistics, mathematical modelling, and scientific analysis.
- Ability to build, validate, and maintain predictive and descriptive models, including machine learning and AI methods, with a scientific and experimental approach.
- Skilled at handling diverse datasets, performing data exploration, visualisation, and story telling for technical and non technical audiences.
- Experience with ML/AI applications