Data Scientist

  • 38923
  • Life - Data Science
  • |
  • Singapore
  • |
  • Jan 21, 2021
Reinsurance
RESPONSIBILITIES
  • Use advanced analytics methods to derive actionable insights from existing and new sources of data
  • Cooperate closely with clients, actuaries, underwriters, client managers, the IT department, other analytics teams worldwide including at head office
  • Apply Machine Learning and Deep Learning methods to interpret all types of data and build solutions to and solve real problems clients are facing today.
  • Play a leading role in the execution of the full modeling cycle, including the integration of data, selection and application of predictive modeling techniques, model validation and deployment, and engagement with clients on results.
  • Develop insurance business solutions based upon insight discovered from data
  • Active participation and management of projects in the fields of statistics, machine learning and deep learning
  • Development and implementation of solutions that enable operational units to increase quantity and quality of new business
  • Supporting and advising the business units in applying the latest research methods and providing a central source for specialized know-how, tools and techniques for data analytics
  • Presentation of statistical, machine learning and deep learning solutions to internal and external stakeholders
  • Networking with already existing data-intensive units in the area of analysis and reporting, as well as with IT to form an analytics community.
  • Collaborate with internal partners in Life and Health and the data analytics centre to leverage capabilities in big data technology
QUALIFICATIONS
  • Preference for Master’s or Ph.D. in data science / advanced data analytics but other fields will be considered including statistics, applied mathematics, information technology, engineering, computer science, or a comparable discipline.
  • More than 2 years of industry data science / AI / ML experience
  • Experience:
  • Very good theoretical knowledge of AI, ML and DL methods
  • At least 2 years hands-on coding in R, Python, SQL (e.g. ETL), etc.
  • Experienced in carrying out exploratory data analysis, model development and visualization in Jupyter Notebooks (Python and R)
  • MUST have demonstrable experience in coding and applying traditional regressions (e.g. GLMs), ML (decision trees, random forest, boosted trees, etc.), natural language processing, DL
  • Visualization in Power BI, D3.js, Dash, JavaScript, etc. is an advantage
  • Working on data science virtual machines on the cloud (Azure, AWS, etc.)
  • Understanding of RESTful APIs and microservices is an advantage
  • Demonstrable Kaggle / Git / analytics blogs and repos are an advantage
  • Experience in insurance/reinsurance industry would be an advantage and specifically on the topics of underwriting and claims automation and fraud detection
  • Strong communication in:
  • Documenting analytics results (e.g. MSWord, PowerPoint, Notebooks, etc.)
  • Verbally explaining analytics concepts and results to non-technical audiences and domain experts and translating analytics results into business solutions
  • Ability to deliver under short but reasonable timelines
  • Capacity for innovation, entrepreneurial mindset, forward-looking, enjoy working in a team
  • Good command of English essential
  • Willingness to travel within Asia for short periods