Data Science & Analytics Engineer

• Team Context

  We are expanding our team at the leading edge of data science & analytics, and we are looking for dynamic, inquisitive individuals to help us grow our expertise in analytics, artificial intelligence, and machine learning. We are looking for collaborative individuals to help us enhance our data practice working to turn research and experimentation into actual beneficial outcomes for our customers and business. If that sounds like you then keep on reading.

  Our Data Science & Analytics team will take the lead on exploring new insights from our data that benefit the customer and Aflac to provide the building blocks for new products, benefits and offerings within the industry. This will involve data discovery, analytics, data visualisation, algorithmic and model development and will contribute to the consolidation and enrichment of our existing data models.

  This high-performing team will operate with the freedom to explore, develop, and learn new insights, prototype and pilot new designs to improve human / machine interaction creating deeper insights for our customers. As a team they will lead on data discovery and analysis, collaborating with local engineering teams and our US colleagues. Solving complex problems through analytics and ML modelling techniques and assisting engineering to turn ideas into reality.  This unique group of analytical thinkers will work on some of the biggest problems for the company and help us to better serve our 50 million policy holders.

  Role Context

  We want an open-minded free-thinking Data Science & Analytics specialist who enjoys solving complex data driven problems within a team environment. We are looking for someone who is self-motivated and driven to look at problems through a different lens, diving deep in to the data to challenge the status quo and educate leadership on the power behind the information which insurance companies hold.

  In joining this team, you will have the opportunity to drive disruptive and market-leading solutions for the world of medical insurance, providing tailored and customer centric solutions for policyholders, agents and employees, as well as have a lot of freedom and fun in the process.

  Key Responsibilities

  • Be curious, have a questioning mindset and help build a team of data scientists to find new insights and prove business value from our data.
  • Freely experiment from conception to prototype, working with in-house engineering teams and third parties to iterate and test model assumptions.
  • Motivate and support the rest of the team as they gather insights and build and train new data models.
  • Work with the data solutions architect to plan how best to turn insights into products from pilot to production.
  • Develop strong working relationships with Data Strategy leaders to maximise the outcomes of the team and the impact to customers.  
  • Solve complex problems in a collaborative and open learning environment
  • Listening to the inputs of others and working towards the best solution that maximises the value to the policyholder, without ego or prejudice

  Skills and experience

  Below is an overview of the skills and experience we are looking for, but remember, don’t rule yourself out if you don’t have everything on the list – it’s your intellect and your attitude we’re really after. 

  Essential

  • Bachelor’s degree. Comparable commercial experience may also be considered
  • Should have 5+ years experience in applied data science
  • Experience in data analysis and visualisation
  • Proven experience of business problem solving through data analytics
  • Strong analytical, statistical experience is required
  • Analytics fundamentals (Data mining, data manipulation, statistical analysis)
  • AI fundamentals (CNN, RNN, Deep Learning, Knowledge graphs)
  • Experience/Knowledge in Machine Learning/ Semantic analysis
  • Familiar with cloud-based technologies (AWS, Azure)
  • Experience programming in one or more of the following: Python, R, SQL, Scala.
  • Excellent written and verbal communication skills 
  • General data engineering principles and data architecture knowledge
  • Experience or the willingness to learn any new data technologies

  Desirable

  • Masters or PhD in a STEM discipline
  • Relevant academic or professional research
  • Experience of MLOPs/Machine Learning Engineering
  • Experience working and collaborating in teams particularly in the data space
  • Experience of stakeholder engagement and playback

  So that’s us. Thanks for taking the time to read this far. We look forward to hearing from you if you fancy joining a new tech innovation company with the agility of a start-up and the stability of a Fortune 500 U.S. company.