Senior Machine Learning Engineer at Bupa
Melbourne, Victoria, Australia -
Full Time


Start Date

Immediate

Expiry Date

05 Sep, 25

Salary

0.0

Posted On

06 Jun, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Jenkins, Machine Learning, Keras, Java, Computer Science, Airflow, Algorithms, C++, Data Engineering, R, Python, Kubernetes, Statistics, Data Structures, Mathematics, Artificial Intelligence, Docker, Utilization, Scikit Learn

Industry

Information Technology/IT

Description

OPPORTUNITY SNAPSHOT:

An exciting, 12 month fixed term opportunity has become availablefor Senior Machine Learning Engineer.
Our Global Strategy set us a clear ambition to be the world’s most customer-centric healthcare company. To bring our ambition to life, it is critical we elevate the focus on digital and data, evolving how we do things to create value for our customers now and into the future.
A key enabler for this vision is the ability to rapidly access, understand and use data to make decisions that improve customer experiences and business performance. The Senior Machine Learning Engineer will play a critical role in enabling Bupa to make use data for automated decision making a scale.
As an accomplished change agent and practitioner of lean, agile ways of working you will be passionate about systems change and using data and analytics to make decisions, measure progress and transform healthcare.
The impact of your work will be measured through the data flywheel: with equal parts’ focus on – doing the right things (value creation), in the right way (data democratisation) and with the right data (findable, accessible, interoperable, reusable).

ABOUT US:

Bupa has a strategic goal of being the most customer-centric digital healthcare organisation, with the use of data as an explicit pillar of this strategy.

Responsibilities
  • 8 years+ relevant experience in the field of Data Engineering
  • 2 years+ experience in Artificial Intelligence or Machine Learning
  • Tertiary qualification in Computer Science, Engineering, Mathematics, or related field
  • At least 5 years of experience in MLOps or related roles
  • Proficiency in Python, R, Java, C++, or other programming language
  • Experience with TensorFlow, Py Torch, Keras, Scikit-learn, or other ML frameworks
  • Experience with cloud platforms, ideally Azure and Databricks
  • Experience with Docker, Kubernetes, Airflow, Jenkins, or other MLOps tools
  • Knowledge of data structures, algorithms, statistics, and mathematics
  • Proficiency in ML Ops, SRE, or DevOps practices
  • Familiarity with health insurance data domains (claims, clinical, provider, member, utilization, etc.).
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