Senior Consultant - Risk Analytics - Melbourne

Last updated 22 minutes ago

The Covid-19 pandemic is creating seismic challenges around the world. Our purpose, to build a better working world, has never been more important. Life at EY has been transformed dramatically but our strong culture of flexible and remote working has helped EY people navigate new ways of working and remain connected with each other and our clients.

A better working world truly starts with the people at EY who are building it every day. Now more than ever we need talented people from diverse backgrounds to help our clients navigate the complexities of this Transformative Age: people with the passion, curiosity and drive to make things better.

The opportunity

We are looking for a Senior Consultant within the Technology Risk team in our Melbourne office, who will focus on data analytics. A person who is passionate about delivering insight through data and analytics. A person who thrives on sharing knowledge and actively seeks to train and educate others on improving how data is accessed and presented to decision makers.

You will be part of a specialist risk data and analytics team with links into the broader Advisory community. This is a key role supporting analytics and broader risk management offerings to our clients. We provide data-driven risk intelligence and bespoke solutions to our clients, through the analysis of transactional or operational data. We are experts in harnessing large amounts of data to identify threats to our clients’ businesses, highlight where failures are occurring and quantify the impact of identified issues.

You can expect to work with top tier clients across multiple industries, including Government, Education, and Utilities.

Your key responsibilities
  • Spread data literacy and enthusiasm for data, analytics and technology
  • Be the translator between technical and non-technical stakeholders
  • Define the requirements and technical specifications and deliver data and analytic use cases working collaboratively with other team members and our clients
  • Conduct data analytic benchmarking using EY frameworks
  • Peer review data and analytic assets providing recommendations
  • Act as a data / analytics subject matter resource (SMR) on one or more of the following topics: data analysis, data migration, data transformation, data science, data visualisation, data governance, and data privacy
  • Work in high-performing multi-disciplinary teams, build internal networks, and supervise and coach staff
  • Develop client relationships, grow networks, and assist identifying and converting engagement opportunities
  • Building strong relationships both internally and in the market. Become a trusted advisor to your clients
  • Mentoring individuals to help them achieve their best, build their capability and manage their careers
Skills and attributes for success

We are looking for people who have most of the following skills and experience and/or have a willingness to learn. Unicorns are also welcome.

  • 3 years of hands-on data analytics, including:
    • Intermediate SQL / data preparation (essential)
    • Reporting design and development experience using one or more tools such as Power BI, Tableau, Qlik, ThoughtSpot, Spotfire, etc
    • Additional programming in languages such as Python, R, C# etc
  • Experience with large data sets, analysing data, extracting relevant information and producing actionable insights
  • Project management skills and experience managing multiple projects
  • Proven experience in collaborating with data engineers, analytics, reporting professionals and data scientists generating actionable insights
  • Strong analytical and business skills, which you can apply to designing data analytics to measure business performance, identify business risks and support decision making
  • Exceptional communication and presentation skills, which you use to explain your analysis approach and insights to technical and non-technical stakeholders at various levels from junior to C-suit
Ideally, you’ll also have
  • Strong interest for data analysis, mathematics, statistics, modelling, data science or AI
  • Experience with cloud-based data platforms such as AWS and Azure
  • Knowledge in data structures and algorithms for processing large volumes of data
  • Some knowledge of risk management, finance, accounting, and ERP systems, although this is not essential