Decisioning Analytics Manager

About the Role

We have an outstanding new opportunity for a Decisioning Analytics Manager, managing a team of 5. The Decisioning, Analytics and Data team use data-based quantitative techniques, in partnership with our colleagues in Marketing and Product, to identify and deliver relevant propositions to AGL customers and prospects.

Reporting to the Manager Advanced Analytics, you will be part of a team that comprises several functions including data science, decisioning, data, enablement and measurement.

This role enables the creation of customer and shareholder value through the interrogation and interpretation of relevant data sets, leading to inferences that enable high-quality strategic and tactical business decisions.

This role supports a broader cultural shift for AGL from Mass to Personalised retailer by providing the analytical direction for a “next best interaction” system across all customer journeys and channels to optimise customer lifetime value, drive productivity and optimise cost to serve.

Key Responsibilities

  • The role is accountable for optimizing the use of AGL’s decisioning platform and other analytics platforms associated with AGL’s customer market operations
  • Leading a team of data scientists, principally working in horizontally aligned scrum teams, ensuring resources and capabilities are aligned to the priorities of the business
  • Providing solutions to complex business problems, devising decisioning approach and developing models using machine learning, predictive and adaptive modelling
  • Setting the direction for the development of predictive and adaptive models used to rank (arbitrate) alternative customer propositions for individual customers
  • Coaching data scientists in the Decisioning Analytics team and across AGL as they develop and implement algorithms to maximise customer value, drive productivity and increase digital adoption.

About You

  • People leadership experience, particularly of analytical teams, is strongly preferred, with an ability to lead teams through a period of significant change.
  • Good understanding for the potential of predictive models to be used to maximise customer experience and value
  • Strong theoretical and practical experience of applying statistical models such as regression, GLM, Neural Networks, Decision Trees, Bayesian Algorithms, Affinity Analysis.
  • Awareness of the strengths and limitations of various advanced analytics techniques (classification, regression, clustering, decision trees etc).
  • Competent with collaborative decision making and problem solving. Comfortable with a co-leadership arrangement, with a shared objective of enabling a high-performing team.
  • Thinks beyond the realms of current approaches and has the tenacity to challenge the status quo, whilst maintaining alignment to the overall business strategy.

What’s in it for you?

You’ll be working in an A-grade building with state of the art activity based working facilities. Being supported by our new flexible ways of working. We call it Smarter Working.

You’ll get the opportunity to work with some of the most engaged and innovative in the business. Being exposed to more opportunities to advance your skills and career.

Working in a company the size of ours the sky’s the limit for your career aspirations and we’re focused on investing in you.

About us

It truly is an exciting time to be part of AGL Energy as we lead the way in generating sustainable energy solutions for all Australians.  With a heritage of over 175 years and listed in the top 50 companies on the ASX, AGL offers a genuinely diverse, safe and supportive work environment, where "actions not words" fosters a culture of achievement and personal development.

How to Apply

Come with us on a journey of exploration and creativity, doing the same things differently, better, faster by encompassing innovation and passion for a more sustainable world.

Apply now to the AGL Careers team via the online application link. For a confidential discussion, please call Bridie Butcher on 03 8633 7914 or

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