Asset Risk & Data Analyst – Hybrid, Water Infrastructure

South Staffs Water

Walsall

Hybrid

GBP 40.000 - 45.000

Vollzeit

Vor 7 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

Family-friendly leave
Pension scheme
Employee assistance program

Zusammenfassung

South Staffordshire Water is seeking an analytical Asset Risk and Data Analyst to support asset management and investment planning. You will transform complex asset data into actionable insights to underpin future investment decisions and improve service resilience, working with engineering, regulatory and operational teams.

The role requires strong analytical skills, data governance, and experience in asset health, deterioration modelling, and risk assessment.

Qualifikationen

  • Experience in asset risk, asset management, engineering analysis, data analysis or investment planning within the water sector or another asset-intensive environment.
  • A good understanding of asset health, criticality, deterioration, failure modes and risk management principles.
  • Strong analytical and problem-solving skills with the ability to convert complex data into meaningful insights.
  • Experience assessing data quality, identifying information gaps and implementing improvement plans.
  • Strong stakeholder engagement and communication skills.
  • Experience producing reports, dashboards and decision-support information for senior stakeholders.
  • Excellent attention to detail and a commitment to maintaining accurate, traceable and robust evidence.
  • Intermediate to advanced Excel skills.
  • Experience using GIS software for spatial analysis and map creation.
  • Power BI report development, including DAX and relational database structures.
  • Deterioration modelling, predictive analytics and machine learning techniques.
  • Python programming.
  • ArcGIS Pro.
  • Knowledge of investment decision-support systems (e.g. Copperleaf).
  • Understanding of value frameworks, whole-life costing and investment prioritisation techniques.
  • Experience within a regulated utility or infrastructure environment.

Aufgaben

  • Support investment planning, asset strategy development and asset management decision-making through robust analysis and evidence.
  • Help develop and maintain our centralised asset risk and investment prioritisation systems.
  • Work with stakeholders across the business to identify, assess and maintain asset risks.
  • Analyse asset performance, condition, criticality and operational data to identify trends, emerging risks and future investment requirements.
  • Contribute to the development of asset health, deterioration, risk and criticality models.
  • Improve the quality, consistency and completeness of asset data held within core business systems.
  • Develop risk reports, dashboards and analytical outputs to support governance, planning and investment decisions.
  • Support the prioritisation of investment needs using transparent, evidence-based methodologies.
  • Maintain clear traceability between asset data, risk assessments, investment proposals and decision outcomes.
  • Coordinate regular asset risk reviews with technical and operational stakeholders.
  • Support the development of evidence required for PR29 business planning and regulatory submissions.
  • Communicate findings clearly to both technical and non-technical audiences.
  • Promote best practice approaches to asset data management and risk assessment across the business.

Kenntnisse

Asset risk
Asset management
Data analysis
Stakeholder engagement
Excel
GIS
Power BI
DAX
Python
ArcGIS Pro

Tools

GIS software
Power BI
ArcGIS Pro
Copperleaf

Jobbeschreibung

South Staffordshire Water is seeking an analytical Asset Risk and Data Analyst to support asset management and investment planning. You will transform complex asset data into actionable insights to underpin future investment decisions and improve service resilience, working with engineering, regulatory and operational teams.

The role requires strong analytical skills, data governance, and experience in asset health, deterioration modelling, and risk assessment.

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