Data Analyst

HM Revenue & Customs; Liverpool; On-site; GBP 30,000 - 45,000; Full time

Job summary

A government department in the UK is seeking a Data Analyst to enhance internal audit processes through data analytics. The successful candidate will collaborate with audit teams, utilize tools like Python and SQL, and promote best practices within the team. Strong project management and communication skills are essential. This role offers a unique opportunity to contribute to a data-driven approach in public sector auditing.

Qualifications

• Experience using analytical tools such as Python, R, SQL, or SAS for data analysis.
• Ability to translate business needs into analytical goals.
• Proven skills in project management and stakeholder communication.

Responsibilities

• Collaborate with data analytics specialists to develop new approaches.
• Identify and promote data analytics best practices.
• Produce detailed reports and dashboards for audit colleagues.

Skills

Data analysis

Project management

Communication

Leadership

Proficiency in Python, R, SQL

Job description

Locations – Liverpool, Newcastle, Nottingham, Preston

Job Description

We are looking for a highly motivated, enthusiastic individual willing to embrace the challenges and demands of supporting HMRC internal audits data analytics ambition. A core aspect of the role involves working with audit teams to understand where data analytics can support delivery of individual audit reviews, working with our customers to acquire relevant data sets and performing/presenting the results of detailed data analysis to audit colleagues and customers.

The Data Analyst will also have a pivotal role is supporting the Data Analytics Manager in delivery of HMRC Internal Audit’s vision to mature the use of analytics in our audit work and helping to drive forward the priority areas and practical steps required to build a more cost-effective data enabled Internal Audit.

Key Accountabilities

• Collaborate with other data analytics specialists across government and the private sector to develop new approaches to data analytics suitable for internal audit.
• Identify, understand and promote data analytics best practice across the Internal Audit unit.
• Carry out advanced data analytics to support internal audit work.
• Produce reports detailing data analysis results for Internal Audit colleagues and customers.
• Develop dashboards and graphical representations of data analysis for reporting to customers.
• Leading on ad-hoc project work as required.
• Use new tools and techniques to develop your expertise for manipulating large datasets, including a range of taxpayer, government, public and commercially available information.

Essential Criteria

To be considered for this role, your application must demonstrate evidence of the following essential criteria:

• Analysis and Synthesis: You can translate business needs into clear analytical goals, apply appropriate methods to analyse data and synthesise insights, and support others to do the same.
• Project Management: You can plan, prioritise and manage delivery with stakeholders and teams, sharing project management tools, techniques and approaches to support effective delivery.
• Communication: You can support or host difficult discussions within the team or with senior stakeholders.
• Leadership: You can lead or mentor others through project delivery and professional development, supporting growth and sharing expertise to build capability across the team.
• Analytical Tools: You can deliver data analysis and/or data science projects using coding languages manually or via an interface, such as Python, R, SQL, Base SAS or SAS Enterprise Guide, to support effective data exploration, interpretation, and insight generation.

Desirable Criteria

• Experience of building capability in non-specialists to understand and use data effectively.
• Be able to demonstrate an appreciation of how data analytics may be applied to internal audit activity.
• Experience of delivering data analytics as part of internal audit assurance.
• Experience of utilising data analytics on enterprise resource planning (ERP) and non-ERP systems.