Working within the CIO team, you will be part of a highly motivated and skilled team of data professionals working to achieve maximum value for our business and customers across all of our investments in systems and technologies.
You will lead the Data Science Team, responsible for delivering business insight through interpretation of large data sets from our financial, operational, network and customer systems. You will work closely with data engineers, data analysts and product owners to solve business challenges, prioritising, scoping and managing a broad range of data science projects.
- Executes & has ownership of the delivery of Data Science activities in ESB
- Prioritises, scopes and manages data science projects
- Delivers tangible value to the business by agreeing KPIs and success criteria
- Accountable for the design and implementation of complex data models and tools, including the use of Artificial Intelligence, to deliver ESB business objectives
- Evaluates the effectiveness & appropriateness of data science tools & methodologies
- Stays abreast of internal and external developments to identify & implement best practice methodologies to deliver against current and future ESB analytics requirements
- Has responsibility for Data Visualisation strategy, policies and guidelines for analytics in ESB, using rich visualisation techniques for storytelling
- Leads and mentors a team of data scientists
- Champions and drives adoption of analytics self-service within ESB. This will include the development and implementation of platforms and technologies to enable the business efficiently consume analytics and insight.
- Supports the Analytics manager in defining and executing the Analytics Strategy for ESB.
Knowledge, Skills and Experience
- Be considered an expert data scientist, with at least 8+ years of relevant experience in successfully planning and executing complex data science projects
- 4+ years management experience in developing people and service capability through resource management, coaching and focused career development skills
- Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Kafka, MySQL etc.
- Experience of working across multiple deployment environments including cloud and on-premise, multiple operating systems and through containerisation techniques such as Docker, Kubernetes, and others
- Substantial Coding knowledge and experience in several languages: for example, R, Python/Jupyter, SAS, Java, Scala, C++, Excel, MATLAB, etc.
- Substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, Alteryx, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, SAP Predictive Analytics.
- Knowledge and experience in statistical and data mining techniques: generalised linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbour Embedding (t-SNE), graph analysis, etc.
- Expertise in visualisation tools like Tableau, Power BI, Business Objects
- Establish best practices around ML production infrastructure
- Have a track record in launching innovative projects, gaining the respect of stakeholders at all levels and roles within the company.
- Microsoft Database technologies (SQL Server, SSIS, SSRS)
- Proficiency with Azure DevOps
- To have an external focus and seek ways that ESB can continue to adapt and improve its use of data analytics in the broadest sense
- Agile development methodologies (Scrum, Kanban)
Above all, you must be innovative in your approach and be able to demonstrate your ability to actively contribute to a team that delivers results. Knowledge of the electricity supply, transmission and generation business is not essential, but would be a distinct advantage.
- A MSc/PhD in Data Science, Mathematics, Statistics, Computer Science or equivalent discipline.
The position is primarily located in ESB Head Office, Dublin City Centre
This role reports to ESB’s Analytics Manager.
1st Septemeber 2020
Note: Please advise if you require any additional accommodations to
assist you if you are called to attend at interview.