Data Scientist (InsurTech)

Proven expertise applying predictive modelling concepts and machine-learning approaches
What you will be doing

  • Increase and spread Data Science knowledge within the organisation (survival analysis, interpretability etc)
  • Develop and manage advanced statistical, predictive, and machine learning models as well as provide technical services to a growing cross-functional team of data scientists, software engineers, underwriters, and actuaries.
  • Help innovate processes such as underwriting or claims by creatively applying cutting edge data science techniques.
  • Drive the advancement of market focused data analytics projects in close collaboration with different parties including marketing managers, underwriters and actuaries.
  • Present results to stakeholders; clearly communicate complex topics
  • Key distributor of knowledge, increasing the interpretability of models through advanced understanding of artificial intelligence and machine learning
  • Participate in cross-countries projects to bring our expertise and develop cutting-edge analytic solutions.
  • Core contributor on global infrastructure (AutoML, visualization, templates etc)
  • Collaborate with the organisations thriving global data science community by being a key contributor on research projects and contribute to local projects.

Who you will be working for

A global insurance consultancy firm with over three decades of experience in delivering data intelligence, technology and marketing solutions. They have recently embarked on a three-year “Journey to InsurTech” to continue to pioneer industry-leading tech solutions.

What we are looking for:

The ideal candidate will come with proven years of subject matter expertise applying predictive modelling concepts and machine-learning approaches within the Insurance or Bioinformatics industry (i.e. identifying bio-markers).

  • Master’s degree in Science (Ph.D. is a plus), Technology, Engineering, Mathematics, Computer Science, Actuarial, Bioinformatics or similar quantitative field
  • 2 to 7+ years’ professional experience in data science with strong programming capacities and advanced knowledge of text mining, artificial intelligences, and supervised/unsupervised machine learning techniques
  • Domain background in Insurance, Bioinformatics, or Genomics is a strong plus.
  • Deep understanding (academic knowledge) of predictive modeling concepts, machine-learning approaches, clustering, classification (e.g. GLMs, Decision Trees, SVM, Random Forests, GBM, PCA, Bayesian Networks, Neural Networks, etc.)
  • Sensitive to interpretability & ethics and familiar with some explanability tools (SHAP for instance)
  • Basics in software development best practice and code/model versioning (git usage, docstring, CI, knowledge of model versioning platforms like MLflow is a plus)
  • Expert knowledge of common data science programming languages such as Python (preferred) or R.
  • You have some experience (even basics) with Docker
  • Experience with database query tools such as SQL (PostGreSQL, MSSQL,etc.) or NoSQL (AZ Cosmo/Mongo/Snowflake)

What you will get in return:

Working in the FinTech industry certainly has its rewards and this role is no exception. Get to work with some of the most talented technologists across the globe, plus a great flexible working programme in place. The business also had zero attrition in the past year which demonstrates its incredible stability and culture.

Please click to apply for this role, we welcome your application!

At Hays Technology, we are shaping the future of recruitment. The rise of AI and machine learning and the need to drive data integrity, compliance and digital transformation make data analysts some of the most valuable members of an organisation. So, whether you are hiring for your team, or looking to take the next step in your data analytics career, we’ll support you every step of the way, so talk to us today.
. #1213255


Job Type
Technology & Internet Services
Digital Technology

Talk to a consultant

Talk to Daen Huang, the specialist consultant managing this position, located in Singapore
#27-20 UOB Plaza 2, 80 Raffles Place

Telephone: +6563030158

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