Data Analyst/Scientist

Job Description

Our Client Scottish Power are currently recruiting for a Data Analyst/Scientist to join their team based in Glasgow on an initial contract basis. For this role ideally they are looking for a candidate with a strong data background as well as various softwaresolutions experience. Please see below for the job description for this one: The key objective of the data analyst/scientist is to support strategic and operational decision making in order to create value and drive out costs by leveraging the value inherent in our organisations data. They will be expected to Explore and visualize the data to present the story of the data in a meaningful way, and to a range of technical and non-technical audiences Manage projects to investigate alternative Historian systems, and the eventual tender process for the replacement system Assist in sourcing, accessing and manipulating data Assist with advanced analytics on data using statistical, descriptive and machine learning techniques Use data to aid simplification of internal processes Effectively present outcomes to stakeholders. The successful candidate will be collaborating with business stakeholders to understand business problems and asking the right questions from which to exploit data. Accountability Statements Manage Data Historian replacement projects and associated data analysis Develop and produce actionable insights from Historian and other SPEN applications, industry and external data sources using a number of different statistical, analytical and machine learning techniques Promote and support analytical decision making across the wider business Provide analytical support to the SPEN Executive team as required Dimensions The role involves the delivery of complex processes and detailed insight across the business and requires a significant degree of stakeholder management. Planning and Project Management including timelines, risks and dependencies and resource planning of various business wide projects are also essential tasks that need to be mastered. A thorough understanding of various data analytical and measurement techniques and the ability to effectively present the outcomes to stakeholders is also essential to deliver robust and actionable outcomes. The scale and complexity of the role is reflected not only by modelling skills in applications and coding such as R, RStudio, Python, SQL and SAS analytics but also in the ability to understand the end to end operational complexity of the data management lifecycle. Skills, Knowledge & Experience Key required skills/experience is shown below Educated to degree level qualification in Data Science/ Analytics, Computer Systems, Mathematical or related scientific discipline Experience in data analysis Experience of managing relationships across functions Experience in data presentation / visualisation tools (e.g. PowerBI, ArcGIS Online) Experience in data query languages, particularly, SQL, Python, R Understanding of the principles of statistical analysis and machine learning techniques Planning and Project Management including timelines, risks and dependencies and resource planning of various business wide projects Stakeholder engagement/management Competent reporting, presentation and self-projection skills Fully pc-literateThe role involves the understanding of complex processes across the business and requires a significant degree of stakeholder management and project management. The role holder will be someone who is organised, and who works in a logical and structured manner. Taking responsibility for the planning of complex pieces of analysis utilising data from multiple sources with several stakeholders. Minimum Criteria Ability to use various software solutions to carry out data analysis and create reports including but not limited to Python, R, and Oracle Ability to effectively present outputs in an appropriate way for the given audience using visualisation / reporting software e.g. PowerBI, ArcGIS Online Proven project management skills and experience Proven relationship management skills, Good verbal skills Strong influencing and stakeholder management ability Highly Numerate and analytical. Strong understanding of the SPEN business model and related functions Educated to degree level in a science or relevant numeric discipline.