Data Scientist

  • 37162
  • Non-Life - Data Science
  • |
  • Bermuda
  • |
  • Apr 2, 2020
Other
RESPONSIBILITIES
  • Designing and implementing effective management and supervisory reporting systems as predictive analytics tools to assist Supervision, Authorisations and Licensing teams in reviewing financial institutions’ prudential returns and other information.
  • Identifying and gathering data from internal and external sources to achieve effective predictive qualitative and quantitative analytics in relation to financial institution solvency, risk management, governance and general regulatory compliance.
  • Extracting statistics from the data warehouse, and carrying out manipulations and analysis on large data sets, comprising of financial returns.
  • Creating detailed reports from data sets, and providing insight for the prudential supervision and stakeholders engagements.
  • Training relevant staff in interpreting the output from the aforementioned automated predictive reporting tools.
  • Performing ad hoc analysis and producing statistical reports at both the financial institution and aggregate industry levels.
  • Identifying opportunities to develop scalable insights for internal and external stakeholders.
QUALIFICATIONS
  • A Master’s Degree or equivalent qualification in Math/Statistics/Econometrics/Actuarial Science or equivalent discipline.
  • A minimum of ten years’ experience in the financial services industry, with at least five in data mining.
  • A deep understanding of machine-learning techniques, including natural language processing and pattern recognition.
  • Proficiency in machine learning applications in finance multivariate modelling using structured and unstructured data.
  • Software engineering knowledge and be experienced with Python, R or other common programming languages.
  • Applied math and statistical techniques in finance and data analysis.
  • Competency in the Microsoft Suite including Advanced Excel Data Modelling.
  • Data visualisation abilities using business intelligence tools such as Tableau and Power BI, and strong communication skills in translating analytical insights.
  • An analytical mind and business acumen.
  • An aptitude for problem-solving.
  • Excellent communication and presentation skills.