Address Description
Amazon is rapidly expanding in Australia. We continue to invest heavily in the creation of a best in class delivery network to delight Australians with amazing customer experiences. Data is at the heart of everything we do and it's especially critical to the success of our logistics teams in their quest to deliver your goods to you faster than ever before. To do so we have created the exciting position of ACES Data Analytics Manager.
In this role you will use advanced analytics technologies, including machine learning and predictive modelling, to support the identification of trends, scrape information from unstructured data sources and provide automated recommendations and data-driven solutions for business decisions across all of Amazon Operations AU.
This position requires excellent business acumen, statistical knowledge, and an understanding of the value proposition/benefits in speed, cost optimization, and global scale. Our environment is fast-paced, and requires someone who is enthusiastic, flexible, detail-oriented, analytical, and comfortable working with multiple teams and competing priorities.
Working closely with cross-functional teams across various departments including, Operations, technology, transportation, learning, topology and customer services, you will work towards driving results for our programs across Australia. In this role you will be required to utilize stakeholder and project management skills to navigate business needs and collaborate with product, tech & leadership teams. Integrating your insights and recommendations within our business strategy.
Key job responsibilities
- Utilised advanced analytical models and or machine learning solutions such as regression, classification, simulation, optimisation and NLP to solve Australia operational business problems.
- Implement cutting-edge techniques and tools in machine learning, deep learning and artificial intelligence to develop create intelligent/automated systems.
- Mining and analysing data from internal data and ingesting external data using APIs or building ETL pipelines for analysis and downstream use in analytics solutions.
- Develop actionable analytics insights to drive leadership decision making on key performance indicators through development dashboards and business reporting.
- Communicating coordinating, influencing teams & Senior Stakeholders to implement data-driven strategies while measuring progress.
We are open to hiring candidates to work out of one of the following locations:
Melbourne, VIC, AUS | Sydney, NSW, AUS
Basic Qualifications
- Bachelor's degree in computer science, mathematics, statistics, computer systems engineering or equivalent quantitative field.
- 3+ years of building and applying statistical models and analytical systems for large-scale application.
- Advanced knowledge of advanced statistical analysis techniques and concepts, and how to apply them to vast data sets.
- Knowledge of Python or other scripting languages.
- Proficiency in writing sophisticated SQL, develop ETL pipelines for training datasets.
- Experience in data visualization & Cloud Computing (Tableau, AWS QuickSight or similar tools).
Preferred Qualifications
- MBA, MS, or MA in computer science, mathematics, statistics, machine learning or equivalent quantitative field.
- Experience with AWS services.
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets (Python, R, Julia).
- Extensive experience in communicating complex technology solutions to senior non technical leadership, gain alignment, and drive progress.
Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement:
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer, and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected attributes.
