Data Insights Specialist

3 days ago

Sydney, New South Wales, Australia CommBank Full time
About the Role

We are seeking a highly skilled Data Insights Specialist to join our Digital Analytics & Insights team within Analytics, Data & Decision Science (ADDS). As a key member of our team, you will play a critical role in helping us make data matter by turning our data into actionable insights.

Key Responsibilities
  • Develop knowledge of the Business Bank and provide analytics guidance to improve the business customer experience across Digital.
  • Use data wrangling methods to deliver insights (including analysis on customer journey, segmentation, profiling, etc) and make recommendations.
  • Create data visualisations, dashboards and/or reports that provide a unified view across the Digital ecosystem to drive actionable insights for better business outcomes.
  • Create visibility of the customer journey including online and offline customer interactions by drawing on existing data sources such as the Group Data Warehouse and Omnia based big data solutions.
  • Pull together disparate pieces of information and compile these into a meaningful story that drives change and informs decision makers.
  • Communicate effectively and persuasively (verbal and written) to project teams and leaders.
Requirements
  • Passion for data: You are naturally curious and driven about how data can be used to identify new opportunities and make impactful business decisions.
  • Analytics: In a nutshell, "you can code". You're likely to have used several of the following languages / environments, and you get excited by the prospect of learning more: SQL, Tableau, R, Python.
  • Communication: You are a confident and capable communicator. You welcome the opportunity to present your work to a wider audience, and are willing to put in the work required to explain it clearly and effectively.
  • Strong attention to detail.
  • Ability to articulate complex analytical requirements and findings in common non-technical terms.
  • Knowledge of visualisation best practices for complex data relationships (e.g. in Tableau, R-Shiny).
  • Relevant experience/knowledge around working with digital data favourable.

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