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Data Scientist




  • Assess project requirements and available data to consider modeling approach;
  • Confirm project requirements by studying user and project requirements;
  • Confer with others on project team to establish a common understanding of modeling issues;
  • Develop modeling plan and seek feedback from client facing team and client;
  • Create high quality models that result in high quality client deliverables;
  • Maintain documentation that allows for complete knowledge transfer to new and existing staff;
  • Coordinate with other team members to either obtain or provide support;
  • Maintain client confidence and protect confidentiality of information;
  • Provide insights to client inquiries and deliver high level of service;
  • Enhance comprehension of team regarding statistical models and statistical methods;
  • Maintain technical knowledge by attending educational workshops; reviewing publications; establishing personal networks; participating in technical societies;
  • Put in a theoretical structure;
  • Managing the local talents and supervising new team members.


Qualifications and Experience

Mandatory skills:

  • Five-year experience;
  • PhD mathematics, predictive modeling, statistics;
  • R or Python;
  • Currently creating snow-flake schemas to increase data access efficiency;
  • Ability to translate data relationships into models;
  • Experience in any industry (e.g. marketing industry);
  • Hands on building predictive models - practical modeller;
  • Modelling experience in a business environment;
  • ETL experience to add attributes (technology used: scheduled SQL scripts);
  • Proven track record working as a consultant in data analytics projects in Financial Services;
  • Familiar with Risk Management approaches and requirements;
  • Intermediate to advanced SQL skills to query and aggregate data;
  • Excellent analytical and problem-solving skills;
  • Fluent English (written/verbal).

Desirable skills:

  • Convey information in a clear and concise manner;
  • Ability to translate data into meaningful and actionable recommendations;
  • Ability to handle multiple, complex projects in a deadline-driven environment;
  • Working knowledge of basic statistical concepts and methods, including regression analysis;
  • Some experience working with MATLAB, IBM SPSS, SAS Business Intelligence or other similar modeling/analytics tools a plus.

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