Principal Data Scientist

4 days ago

Sydney, New South Wales, Australia SiteMinder Full time
About the Role

As a Principal Data Scientist at SiteMinder, you will play a pivotal role in shaping our data science strategy and driving innovation across the organisation. You will act as a technical expert within the data science team, contributing to the development and implementation of cutting-edge solutions to address business challenges.

Key Responsibilities
  • Thought Leadership: Establish strategic goals and priorities for data science initiatives that align with SiteMinder's overall business strategy.
  • Technical Expertise: Apply deep technical and data analytics knowledge to design and execute proof-of-concepts and prototypes.
  • Experimental Frameworks: Develop robust experimental frameworks to validate hypotheses and assess the viability of proposed solutions.
  • Data Mining: Mine very large data sets from multiple sources for a variety of business situations and discover actionable insights for our clients.
  • Emerging Technologies: Continuously evolve and integrate emerging tools and technologies to enhance SiteMinder's data science capabilities.
  • Data Science Advocacy: Be a data science advocate and inspire enthusiasm among others about the potential of analytics and its transformative possibilities.
  • Innovation and Creativity: Foster fresh perspectives, drive innovation, and leverage creative solutions.
  • Stakeholder Engagement: Engage with stakeholders across the organisation to understand business requirements and translate them into data-driven solutions.
  • Communication and Business Engagement: Demonstrate outstanding communication and business engagement skills, educating non-technical audiences on the value of data science and guiding them on the 'Data Journey'.
Requirements
  • Advanced Degree: Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Mathematics, or a related data science field.
  • Experience: 5+ years of experience in advanced data science platforms and machine learning engineering.
  • Programming Skills: Strong hands-on capability in general programming (Python and/or R).
  • Machine Learning: Thorough understanding of machine learning algorithms and deep neural networks (TensorFlow, Keras, and PyTorch).
  • Data Synthesis: Proven ability to synthesise complex data based on various business situations.
  • Cloud-Based Environments: Experience with cloud-based environments, particularly Databricks.
  • Productionizing Data Science Solutions: Proven track record of successfully productionizing data science solutions.
  • Technical and Data Science Expertise: Extensive technical and data science expertise, sharp strategic and analytical abilities, strong record of professional accomplishment and leadership.

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