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Machine Learning and Personalisation Lead

  • LocationNorth Sydney, NSW 2060
  • Work TypeFull Time - Permanent
  • Positions1 Position


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  • Job no: A8XPJ
  • Categories: Commercial Operations, Customer Lifecycle Management

At Vodafone, a TPG Telecom brand, we put our customers at the heart of everything we do to give Australians more choice and freedom to connect the way they want.

We are looking for a Machine Learning Solutions Specialist to join our CLM team based in TPG Telecom North Sydney head office. The core goal of this role is to bring machine learning science and engineering expertise to a team of data scientists. In this role you will get a chance to design, build and scale the core components of this system. This includes model deployment pipelines, containerisation and productionisation of applications to support complex data science use cases and personalisation. In addition, you will be responsible for building and scoring machine learning models and help optimise automated testing and monitoring of deployed models.

Key Responsibilities and Tasks:           

  • Build and refine a robust Machine Learning pipeline to ensure models are responsive to changes and trends in the data.
  • Maintain ML applications required for optimal scoring of models using AWS technologies.
  • Develop mechanisms to optimise automated testing and monitor business critical analytics workloads.
  • Key contributor to the architectural design of the Data Science environment in AWS. Provide technical expertise to Data Ops and Technology teams throughout this project.
  • Help develop the governance and build frameworks for the team to operate in.
  • Develop NLP for structured and non-structured data from call centres (voice & text) and network.
  • Deploy propensity models e.g churn and propensity to buy products.
  • Design and implement a system to securely and reliably send modelling data to third-party systems.
  • Identify and streamline legacy processes through automation and re-engineering.
  • Be active participation in deployment and implementation activities for data engineering solutions.
  • Work closely with BI, data operations and external consulting firms to inhouse Data Science products including, next best action engine.

 Knowledge & Experience:

  • Computer science, maths, engineering, statistics, IT or related degree.
  • You are an experienced engineer and data wrangler who enjoys building and optimising machine learning systems.
  • At least 4 years’ experience building and maintaining machine learning pipelines with modern tools such AWS Glue and Airflow. Experience with personalisation engineering a plus.
  • Strong experience with building the cloud infrastructure required for world-class machine learning on AWS, SAS or similar. That would include tools like Kinesis, EMR, S3, Athena, Redshift and ElasticSearch. Familiarity in NLP and entity recognition are a plus.
  • Proficiency in statistical programming languages (R or Python).
  • Experience with big data tools such as Teradata or similar a plus.
  • Experience managing releases and data applications changes. Experience with GitHub, stash, bamboo or similar.
  • Interest in working with data streams using tools such as Kafka, and Spark Streaming.
  • Familiarity with marketing campaign execution engines (SAS Enterprise Guide/Management Console or equivalent) desired.
  • You'll be excited by the prospect of designing and optimising our company data science architecture and applications running on it, to support our next generation of Analytics and ML products and initiatives.
  • Customer focus and passion for delivering exceptional Analytics products.
  • Experience working in Agile teams.

With Vodafone, we are committed to attracting, developing and retaining the best people by offering a flexible, diverse and inclusive workplace where hard work is truly rewarded. You will have access to fantastic benefits as part of a global company, including generous leave policies, leadership development programs and opportunities to grow your career. You’ll be faced with loads of variety where no two days are ever the same in a collaborative work space that helps drive innovation. 


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