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Data Scientist

2 weeks ago

Melbourne, Victoria, Australia SEEK Full time $90,000 - $120,000 per year

The Team

The Candidate Quality team consists of Data Scientists, AI Engineers, and Product
Managers, operating as a specialized unit within SEEK's broader Artificial Intelligence &
Analytics division. We follow a quarterly planning cycle in pursuit of our mission: helping
hirers connect with quality candidates. Our work encompasses developing machine
learning models for candidate quality scoring, leveraging AI to enhance role requirements,
selection criteria, and candidate matching, and supporting candidate discovery.

The Role

As a Data Scientist at SEEK, you'll be part of a fast-paced, supportive environment where
you can make a real difference. You'll work on complex challenges that have a direct impact
on people's lives, helping us evolve our business and reach new heights.

Successful performance in this role will be demonstrated through the business value
contributed by developed and supported products. Further, the successful candidate will
be expected to stay up to date with emerging techniques in natural language processing
and machine learning, and be deeply involved in a culture of continual improvement.

This role will report to a Senior Data Scientist / Principal Data Scientist within AIPS. AIPS has
a matrix structure where your direct line manager will act as a coach and technical mentor
but your day-to-day activity will be determined by the squad priorities.

Key Responsibilities

  • Forming clear data addressable problem statements related to candidate-job matching and qualification identification
  • Gathering, validating and understanding data relevant to job requirements and candidate qualifications
  • Designing and building data transformation pipelines and machine learning algorithms to improve matching accuracy and relevance
  • Working with product management and other business stakeholders to review and iterate data products to better serve both hirers and job seekers
  • Developing models that can effectively identify and highlight relevant skills and qualifications from unstructured text data
  • Evangelising appropriate ML methods and explaining them, and their associated benefits and limitations to team members from Engineering and Strategy.