Data Analytics Manager

Energy Retailer
- Lead a team of Analyts
- Melbourne, AU [WFH/Office Hybrid]

**Through an industry-leading commitment to innovation, our client is investing in Australia’s energy future by developing the full portfolio of energy resources, including cleaner energy, renewables and energy efficiency, looking ahead by creating new products and services to help brighten the lives and businesses of millions of customers nationwide.**

As our client continues to build their internal capabilities, they also look at increasing performance whilst providing a framework for which the retail energy business can innovate and grow and are seeking a
**Data Analytics Manager **to lead and deliver a new team of data analysts to use data to inform and support decision-making for the Retail Energy business line to support the growth and understanding of the Retail Energy market and team performance.

**Responsibilities**
- Identify projects and business questions that need to be answered by data and insight and manage the associated workload
- Work with users within the Retail Energy business unit to gather business requirements and turn these into wireframes, and data requirements and build solutions that meet expectations whilst incorporating and suggesting improvements
- Work with structured, semi-structured and unstructured data
- Support ad-hoc requests and act as the point of contact for the Retail Energy Business Line for all things data and insight
- Turn data into actionable insights that can support and drive impactful business decisions.
- Identify opportunities to optimise and drive improvements to the data and insight platform for the Retail Energy business unit
- Work with the Corporate Strategy and ELT to measure the impact of business strategy
- Communicate results and influence key, business leaders.
- Create high-quality and engaging data visualisations that effectively communicate complex datasets to key internal stakeholders

**Qualifications & Expertise**
- Previous leadership experience
- A Bachelor's degree in Engineering, Computer Science, Mathematics, Statistics, Economics or other quantitative disciplines.
- Comfortable in at least one scripting language - Python (preferred)
- Knowledge and experience using common open-source languages for data modelling/ETL, e.g. Python and SQL
- Familiarity with code and package management tools such (E.g. git, Conda)
- Ability to detect patterns and relationships in data using a range of Data Science techniques (e.g. unsupervised and supervised learning, principal component analysis, time-series modelling, neural networks, spatial modelling etc.)
- Ability to communicate with both technical and non-technical audiences when translating complex technical analyses into actionable insights and recommendations
- Strong data analysis skills and experience building scalable data pipelines
- Experience working with cloud infrastructure
- Strong background working in Tableau for scalable solutions
- Experience with business requirements gathering and agile ways of working
- Data Analytics experience and knowledge of machine learning, forecasting and statistical techniques

**On offer is the opportunity to develop your career as part of a growing, successful, and innovative organisation that offers a host of additional benefits including**:

- Competitive remuneration;
- A safe and sustainable workplace
- Equal opportunity employment;
- Personal development and training opportunities;
- Flexible work arrangements and
- An award-winning employee recognition program.

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**For further information, please contact**:
**Ivan Pignataro**

**D’Arcy Weil**
St James Building, Mezzanine

555 Bourke Street, Melbourne VIC 3000

**T**:
+61 3 9999 7409

**M**: 0416 507 856

Disclaimer:

- The above information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job._