Apprentice Data Analyst

at  Detectronic Ltd

TURN DATA INTO ACTION!

Detectronic is looking for an Apprentice Data Analyst eager to make an impact. Use cutting-edge analytics to detect trends, predict issues, and create solutions that contribute to environmental protection and smarter infrastructure.

ABOUT US:

Detectronic is a UK specialist in Wastewater Network monitoring, providing the most cost effective and technologically advanced flow and level monitoring systems in use today, enabling customers across the water sector to prevent pollutions through the provision of asset intelligence. Detectronic designs and manufactures its own range of patented products and provides data management services through its dedicated data centre. It does this via the installation, repair and maintenance of its product lines which include a range of flow and level monitoring devices.
Detectronic is an Adler & Allan group company. From its headquarters in Colne, Burnley, Detectronic now serves a significant proportion of the UK’s water industry and has thousands of asset installations at various stages within the asset lifecycle across the UK. The businesses reach continues to expand, and the senior leadership team have exciting growth plans for domestic and international markets.
Adler and Allan are committed to fostering diversity and inclusion in our workplace. We proudly embrace equal opportunities for all applicants, regardless of race, colour, religion, sex, sexual orientation, gender identity or national origin. If you require any support with your application, whatever the circumstance, please let us know.

• Post-install data validation.
• Screening data for profile changes and reporting to customer.
• Analyse data sets taking account of different data structures and database designs
• Implement the stages of the data analysis lifecycle
• Apply principles of data classification within data analysis activity
• Assess the impact on user experience and domain context on data analysis activity
• Identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
• Undertake customer requirements analysis and implement findings in data analytics planning and outputs
• Identify data sources and the risks and challenges to combination within data analysis activity
• Apply organisational architecture requirements to data analysis activities
• Apply statistical methodologies to data analysis tasks
• Apply predictive analytics in the collation and use of data
• Use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
• Collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
• Select and apply the most appropriate data tools to achieve the optimum outcome