Data Scientist

£43,001 - £47,779 per annum, flexible hybrid working pattern (2 days per week in office), 35-hour week, 39 days annual leave (including statutory days), good pension scheme and other generous benefits

This post is subject to DBS clearance.

Hays Technology are working in partnership with a large public sector organisation in Coalville to recruit a Data Scientist to join their Technology team on a permanent basis.

The successful candidate will focus on leveraging data analytics to drive insights and improve the quality and efficiency of services by cleaning and organising data. This role involves working closely with various stakeholders to extract, analyse, and interpret complex data sets to inform decision-making and policy development.

Principal duties and responsibilities:

Collect and analyse data from internal systems (tenancy, maintenance, finance) and external sources (e.g. census, public datasets).
Clean, structure, and validate data to ensure accuracy and usability.
Build models to forecast housing demand, rent arrears, and maintenance needs.
Create dashboards and reports to communicate insights to non-technical stakeholders.
Assess the impact of housing initiatives and recommend improvements.
Use ML to optimise resource allocation, predict tenant behaviour, and automate processes like arrears risk scoring.
Maintain data quality, security, and compliance with GDPR and other regulations.
Work with housing officers and managers to translate operational needs into data-driven solutions.In order to apply, you must have the following skills and experience:

Industry certifications in data science or related fields (e.g., Microsoft Certified: Azure Data Scientist, Google Professional Data Engineer) or equivalent experience.
Experience working as a data scientist, ideally within social housing, public sector, or a related industry.
Experience working with social housing data systems (e.g., MRI, Northgate, Civica, or Orchard) and the ability to apply advanced analytics to operational challenges in housing (desirable).
Demonstrated experience in using machine learning, predictive modelling, and statistical analysis to solve real-world problems.
Expertise in statistical modelling, predictive analytics, clustering, classification, and regression techniques.
Strong background in data mining, pattern recognition, and anomaly detection to improve service delivery.
Proficient in Python, R, or other relevant programming languages used for data science.
Strong skills in SQL and experience working with large databases and data warehouses.
Ability to create intuitive and informative visualisations using tools such as Power BI, Tableau, or similar platforms.
Familiarity with cloud-based data platforms (e.g., Azure, AWS) and deployment of models in a production environment.

If you have the relevant experience and would like to apply, please submit your CV.

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