Lead Data Scientist

  • Full Time
  • Melbourne

Website DNA Talent

Lead Data Scientist

As a Lead Data Scientist, you will be responsible for developing and implementing data science strategy – which spans analytics through to machine learning across product development, performance improvement and risk management.

If you’re driven to succeed, have a desire to provide exceptional service and want to work for a company you’d be proud to tell your friends about; this is the perfect opportunity for you.


  • Data Strategy
    • Contributing to the development of our client’s approach to the collection and use of data assets across the business.
    • Ensuring the quality of data and information across the business and providing the basis of high trust in all of data assets.
    • Selection of quantitative and qualitative methodologies in business decisioning.
    • Input into the development of the data and BI infrastructure, ensuring the business is equipped to make data-driven decisions and that the tools, methodology and infrastructure will scale with the business.
  • Analytics
    • Development and implementation of Machine Learning approach across all business applications and domains – from pricing to risk management and beyond. This will include:
      • Developing and training machine learning models to scale workflows for both customers and internal users.
      • Support new product development ideas by providing guidance on the best use of AI/ML to develop products or supporting tools.
      • Create the technical vision for the team on both data analytic foundations and advanced models.
      • Working with the business across research and day-to-day activity to provide tools, insights and BI to support decision making.
    • Using data and analysis techniques to identify:
      • Product improvements – including cross sell / up sell, improved personalisation, pricing and risk management
      • Process improvement – including funnel optimisation, churn / loss reduction, improvements to the business’ forecasting approach
      • Monetisation opportunities of data assets


  • 5+ years of experience in BI / Data Science in a high growth environment
  • Strong mathematical & numeracy skills
  • Extensive experience in SQL, noSQL, Python / R / Matlab
  • Understanding of ETL framework and ETL tools including Skyvia, FiveTran, Apache Airflow
  • Excellent analytical skills – the ability to identify trends, patterns and insights from data
  • Experience with ML / AI models and their application to business problems such as churn, cross sell, risk assessment and other
  • Experience interpreting data and analysis to translate these insights into actionable outcomes / business decisions that improve strategy, product and operations.
  • A background in SME lending, challenger banks, and other disruptive fintechs will be a natural advantage in this role. A person who has practical experience in developing risk scorecards and automating underwriting processes will also have a head-start
  • Experience in bank or non-bank financial institution lenders is highly advantageous


  • Loves challenging the status-quo
  • Ability to work autonomously yet collaboratively
  • Strong attention to detail
  • Presentation skills – ability to write and speak clearly to easily communicate complex ideas in a way that is easy to understand
  • Structured problem solving skills and comfortable with ambiguity
  • Be able to continually balance speed, perfection, and actionable outcomes from your analysis
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