Data Scientist

Posted 15 March 2019
Salary Up to £40,000
LocationLondon
Discipline Renewable Energy & InfrastructureDigital & Technology
ReferenceSG33123
Contact NameWill Mackay

Job description

The Company:

A leading company in the renewable energy sector with many MWs of renewable energy assets across the UK. They have been a key leader in controls, automation and data science and are looking to expand their team with a talented new data scientist looking to grow their career in the sustainable energy sector.
 
 

The Role:

The Role: Our client is now looking to add an enthusiastic and passionate Data Scientist to our team who is keen to tackle real world and commercially-crucial challenges. The candidate will collaborate very closely with the wider team of commercial analysts and optimisation experts. This way the candidate will gain deep insight to all the  optimisation activities. The candidate will learn from best practises in academia and within the industry 
 

The Person:

  • Highly quantitative degree from a good university, e.g. Maths, Physics, Computer Science, Engineering, Operational Research – Masters equivalent or PhD • Fluent in Python, ideally experienced in the use of the following: 

  • Data manipulation (pandas) 

  • Numerical analysis (numpy, scipy) 

  • Machine learning (sklearn, keras) 

  • Practical knowledge in applying machine learning techniques 

  • Well-versed in model construction and evaluation 

  • Experience with developing deterministic and stochastic models 

  • Practical work experience with time-series data, dealing with problems such as autocorrelation, non-stationarity etc. 

  • Familiar with APIs and data scraping 

  • Experience with effective data visualisation

 

Desirable experience: 

  • Experience in database design, construction, and interaction 
  • Experience with big data packages such as Spark and Hadoop 
  • Understanding of real-world physics and engineering associated with supply and consumption of electricity 
  • Working within fast-paced commercial environment with high uncertainty 
  • Working within the energy sector
  • Rapid prototyping within an R&D environment