Bluefin Resources

Data Scientist (BB-71923)

Found in: Neuvoo AU


The Company

My client is one of Australia's largest retail groups who are award winners for their innovation and customer focus and their multi-channel initiatives. They are embarking on their next generation of growth - their family of leading brands are well respected and highly visible throughout Australia, New Zealand and the world and Data & Analytics is one of the most critical enablers of their future success.

The Role

Reporting in to the Head of Analytics, you'll work closely with key stakeholders across Customer, Product and Pricing teams to make informed decisions through the application of predictive analytics and machine learning techniques.

Working with a broader Analytics Team, you will be responsible for the end-to-end data science execution including scoping, building, testing, implementation, maintenance, tracking and optimisation of predictive models.

Key Responsibilities

  • Partnering with key stakeholders to identify data led solutions and insights to drive customer and product pricing strategies
  • Build predictive models and machine-learning algorithms to calculate elasticity and optimise price utilising customer, product and transactional data
  • Applying advanced statistical and machine learning techniques including GLM, Random Forests, GBM, xGBoost, etc
  • About You

  • Minimum of 2-3 years ' experience in developing predictive models in commercial environments (exposure to pricing is a big plus)
  • Tertiary qualified in relevant discipline (Statistics, Data Science, Mathematics, Computer Science)
  • Proven commercial experience in statistical and machine learning modelling, with experience manipulating and 'making sense' of big data from disparate systems.
  • Exposure to Big Data platforms, such as Data bricks or Spark
  • Experience with SQL essential; exposure to Azure or GCP a big plus.
  • This is a great opportunity to work with a market leading brand that offers excellent training and development to support continuous learning and careers opportunities.

    Please apply on-line below

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    Reference Number: BBBH41919_161295282556543 Reference Numbe: Contact Details: Marie Thow

    calendar_today7 hours ago

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