Senior Data Analyst - Collections

Position summary

A growth focused position centred around the continuous development of business optimisation and collection performance; responsible for assisting in the maintenance and management across automated platforms developed in SAS – including data modelling and predictive analytics.

The analyst will work closely with internal stakeholders within a small team to provide strategic insights and changes under a Question, Data, Analysis and Insights framework (QDAI) – focusing in continuous process improvement and automation.

Furthermore, the analyst will also work closely with key internal stakeholders where detailed analysis and reporting is required on an ad-hoc basis; prioritising these requests with the wider strategic objectives and management stakeholder expectations.

Main Duties and Responsibilities:

· Maintains positive working relationships with peers through clear, respectful communication that promotes PRA Australian culture

· Works with internal/external stakeholders, participates in business meetings when required

· Engages in the monthly one-on-one processes by providing feedback and identifying opportunities for development

· Complies with PRA Australia’s corporate policies and procedures

Business Performance:

· Partners with analytics team to ensure predictive scoring models/strategies align with business objectives, strategies, and requirements

· Works independently and/or directly with business leaders to implement strategic changes to underlying automation under a continuous improvement cycle

· Participates in the Question, Data, Analysis, Implications (QDAI) cycle to provide strategic insights; continuously challenging “Business as Usual” (BAU)

· Keeps abreast of industry changes, “Best in Class” approaches, including their applicability to PRA Global

Strategy Monitoring and Reporting:

· Develops, maintains and reviews reporting across the PRA Australia Power BI platform

· Capitalizes on data to provide sound business recommendations and decisions

· Able to build predictive modelling in both SAS and SQL with a minimum of Operational input

Experience/Qualifications

Essential

- Significant experience in SQL

- Expert skills in SAS/Python or R programming language

- Strong or advanced skills in Excel

- Strong analytical and problem-solving skills with a proven ability to conduct root cause analysis across complex business processes with a minimum of operational input

- Experienced application and management of predictive modelling methods/frameworks

- Sound communication skills with the ability to persuade, influence and built rapport with others

- An interest in imparting specialist knowledge and build capacity in others across the business

· Tertiary qualifications in business, statistics, or Information Technology

· Knowledge in retail credit and receivables management

· Expert knowledge in Power BI or SQL Server Reporting Services (SRSS) programs