mentoring other scientists, engineers in the use of ML techniques BASIC QUALIFICATIONS - 5+ years of data scientist experience - Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab) - Experience with statistical models e.g. multinomial logistic regression - Experience in data applications using large scale distributed systems (e.g., EMR, Spark More ❯
heart of our decisions Future Focused - we accelerate change Curious - we turn knowledge into action Role Purpose The Data Analyst will play a key role in advancing forecasting and modelling efforts by managing, analysing, and optimising large datasets across renewable, conventional, and storage assets globally. Working on asset revenue forecasting, power dispatch modelling, or power markets data, the … enhancing the company's global asset performance and revenue strategies. Responsibilities Knowledge Structures poorly defined problems, gathers feedback, and solves them effectively. Defines hypotheses and appropriate analysis approaches. Ensures statistical validity of results while avoiding common pitfalls. Develops deep technical expertise and emerging domain knowledge in forecasting or dispatch modelling. Provides specialist skills in data analysis, visualisation, and data … evolving their skills. Impact Performs defined and repeatable tasks with limited guidance. Independently formulates new analyses and project components. Carries out independent analysis on specific areas of forecasting or modelling projects. Delivers high-quality outputs on time, recognised for accuracy and reliability. Demonstrates strong proficiency in SQL or Python for data handling. Supports data governance and quality assurance activities. More ❯
up to date with the latest techniques. To be successful, you'll need strong analytical skills to identify key value drivers and model potential scenarios and be familiar with statistical methods to we are robust and credible in our efforts to take an insight-led approach to inform our decision making at a strategic level. Key Responsibilities: Analyse relevant … that we can research through our data to inform strategic decision-making Demonstrable experience of having delivered actionable insight that led to significant value creation Skilled and experienced in statistical analysis and modelling, proficient in data wrangling and data feature engineering; experienced in relevant data technologies such as Azure, DataBricks, PowerBI, and coding languages such as Python, SQL More ❯
career the that of a Data Scientist. This builds on the knowledge of the Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statisticalmodelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods More ❯
