Location: Melbourne, VIC
Duration: 4-6 months
Telstra has millions of customers who use a variety of products and services. They collect large amounts of data at various levels both from internal operations and external services. A large part of this data includes customer interactions data with their contact centres. At Telstra, their mission is to champion the customer and develop products and services that will help enhance their customers’ experiences. They use several open-source and vendor tools to convert this data to a format suitable for performing analytics. With recent research advancements on AI based deep learning solutions to this problem, they would like to explore the possibilities of effective information extraction and optimising operability and efficiency of their customer interactions.
Research to be Conducted
Telstra has large amounts of customer interactions data in various forms and formats. This research looks to adopt some of the state-of-the-art techniques for extracting information effectively from voice interactions and complaints data. The research will essentially involve all aspects of data analysis – prepare, explore, process and analyse data to derive actionable insights. Further, convert these insights into an automated feedback system that will continually improve their customer interaction systems and enhance their customers’ experiences.
If you’re a PhD student and meet some or all the below we want to hear from you. We strongly encourage women, indigenous and disadvantaged candidates to apply:
- Machine Learning, deep learning, NLP/Text Analytics and AI techniques
- R/Python/Java/Scala Programming
- Understanding of speech analysis and information extraction techniques
- Knowledge of customer experience domain is a plus
The intern is expected to collaborate with Telstra staff and provide data science capability. The project is expected to provide information extraction, predictive models, optimise usage models and quantification of value from AI driven decisions that will improve their customers’ experiences.
The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.
It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner. The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
18 December 2019
APR – 1178