Optimizing Job Matches

2 weeks ago

Melbourne, Victoria, Australia beBeeDataScientist Full time $96,000 - $144,000
About the Role

We're seeking a skilled Data Scientist to join our Search team within the AIPS group. This is an exciting opportunity to work with a diverse team of experts to solve complex challenges and drive meaningful outcomes in search and recommendations for job seekers across global platforms.

You'll collaborate with product managers, designers, engineers, and data scientists to design and implement intelligent matching systems that connect the right candidates with the right opportunities. If you thrive on solving ambiguous problems and enjoy working with smart, motivated peers, this role is perfect for you.

The Team

Our Personalisation team is a specialized unit within SEEK's Artificial Intelligence & Analytics division. We build sophisticated machine learning models, adaptive interfaces, and intelligent content systems that truly understand each candidate's unique career journey. Working in quarterly cycles, we're at the forefront of personalisation technology—developing deep candidate insights that directly impact how job seekers connect with life-changing opportunities.

What You'll Do

Business Impact & Collaboration
  • Collaborate with AI Product Managers, Software Engineers, and fellow Data Scientists to solve business challenges and align projects with strategic goals
  • Design, develop, and test new solutions that improve the job search experience for millions of users
  • Work within quarterly planning cycles to develop roadmaps focused on R&D for optimal job matching
Model Development & Innovation
  • Create and enhance models to improve candidate/job matching for search and recommendations
  • Perform feature engineering and hyperparameter tuning to optimize model performance
  • Contribute to the design and implementation of search systems that operate at global scale
Performance & Validation
  • Ensure models meet business objectives through comprehensive online and offline testing, including A/B tests
  • Perform offline evaluation of search systems and contribute to online experiment design
  • Implement ongoing monitoring to maintain model performance and identify improvement opportunities
Data-Driven Insights
  • Collect, validate, and analyze data to identify challenges and opportunities for improving search and recommendation capabilities
  • Translate complex data insights into actionable recommendations for product and engineering teams
  • Support evidence-based decision making across the Search team
Qualifications
  • A strong foundation in machine learning, statistics, and data analysis
  • A Master's or PhD in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field
  • Hands-on experience in model development, feature engineering, and optimisation
  • Proficiency in Python, SQL, and common data science libraries (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch)
  • Familiarity with ranking algorithms or personalisation techniques
  • Experience in A/B testing, experimental design, and evaluating model performance offline and online
Additional Information
  • Permanent Perks: Annual Performance Bonus Plan, flexible working, paid and unpaid leave benefits, support for parents

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