Data Scientist

Data Scientist Role Overview Data scientists explore data using innovative statistical, analytical and machine learning approaches to provide actionable insights which will help create new, high-value customer propositions. The data scientist will be responsible for creating and incrementally improving data products, focused on particular customer outcomes, during the early discovery and design phases. Being a key member of an agile product team, the junior data scientist will closely collaborate with business domain experts to understand raw data and its business context then apply data science techniques to develop valuable, actionable insights, algorithms or models which will be tested with customers. The data scientist will be comfortable in applying data science techniques such as data mining, statistical and cluster analysis to large data sets using cloud computing resources, big data frameworks and open-source packages. They will understand both the theory and have practical experience building accurate predictive models using a range of machine learning algorithms (e.g. regression, decision tree, k-means). The successful candidate will be able to effectively communicate complex, technical information to non-technical stakeholders. Where necessary the role would include on-the-job training and coaching from experienced data scientists in the team and begin a development path to becoming a future technical leader. Responsibilities: Set up an exploratory environment, join multiple large data sets (weather, demographic, sensor) to enable an in depth understanding of energy use in 100'000's homes Generate statistics, clusters and insights about the customer group to help direct future data enabled products and services Help prioritise the products and services and use data to support these decisions Build models, algorithms or novel approaches to automating data enabled products and services for customers, track the impact of these services to support iterative development Build relationships with the wider data science community in BlueLab and EDF Energy Support the industrialisation of models and algorithms from R&D Principal Accountabilities: Apply scientific methods through experimental design, exploratory data analysis and hypothesis testing Lead on the technical solutions for proof-of-concept projects, experiments and trials using advanced analytics and machine learning Understand the business drivers of use cases and helping to confirm the appropriateness of data science techniques in developing solutions Scrape, explore, cleanse and visualise big datasets using leading tools and technologies Engineer new features for models from raw data Demonstrate best practice programming and code optimisation using Python Develop predictive and prescriptive models which utilise supervised or unsupervised machine learning algorithms Deliver actionable insights which provide positive commercial impact to the wider Customers Business Unit Document and communicate findings from analysis to key stakeholders within the organisation Contribute to the wider Customer Data Science community by sharing knowledge, experience ideas and findings Continually develop technical capabilities through on-the-job coaching and mentorship from more experienced data scientists in the team Drive the Trust agenda forward by ensuring that all decisions affecting customers meet the Trust Test, deliver the desired customer outcomes and provide customers with the ability to make informed choices Knowledge, Skills, Qualifications & Experience: Essential: Strong understanding of applied maths, statistics, data mining techniques and algorithms Good programming knowledge in SQL, Python or other advanced programming languages Experience with big data framework such as Hadoop or Spark Highly experienced with cloud computing environments (AWS) Familiarity with Jupyter notebooks Knowledge of schema, technical tables and application logic for SAP ERP systems (particularly SAP CRM and SAP ISU) Skilled in extracting, transforming, wrangling and cleansing large datasets for the purposes of data analysis Proven work experience in designing and building accurate predictive and prescriptive models Skilled in applying appropriate machine learning algorithms across a range of problems including both structured and unstructured data Skilled in creating compelling data visualisation to communicate complex analytical findings Ability to inform and influence, and to drive awareness of the benefits of data analytics Customer mindset with focus on delivering high quality analysis on time Able to effectively communicate complex, technical information to non-technical stakeholders Able to proactively identify opportunities for data analysis to create value Analytical mind-set with positive attitude to problem solving Strong written and verbal communication skills Demonstrated ability and flexibility to work in a fast paced and demanding environment Transparent and open in their approach and willing to continually improve through acting on constructive feedback Critical thinker who is willing to use evidence to challenge prevailing systems and processes Experience and knowledge of key functions of an energy supplier (e.g. customer services, digital channels, sales & marketing, debt recovery, commercial strategy or finance) Desirable: Highly experienced with cloud computing environments (AWS) Experience in cutting edge analytical techniques including deep learning algorithms, neural networks and natural language processing Ability to implement novel analytical techniques Experience of agile working practices and managing agile projects (Scrum, Kanban) Open minded and flexible approach to problem solving - questions currently accepted approaches Essential qualifications & Experience: An academic background in statistics, applied mathematics, computer science, engineering or physical sciences