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Data Scientist - Pretoria

JOB DESCRIPTION

  • Involvement in engagement with stakeholders to understand their business challenges and advise on practical analytics solutions.
  • Collaborate with key stakeholders within the data value chain, external and internal, to ensure that the appropriated data sources and data structures are in place for building analytics solutions.
  • Research, develop and implement appropriate statistical / mathematical / machine learning models as needed.
  • Keep up to date with latest technology trends.
  • Communicate results and ideas to key decision makers.
  • To generate and maintain data assets and utilize these to develop descriptive analytics and predictive models.
  • Use advanced analytics techniques to solve business problems in cooperation with business.
  • Seek out initiatives to enhance companys capability in the data science field.
  • Contribute to the successful achievement of companys vision, strategy and business plan, by assisting with the resolution of problems that pose a threat to the Company of not achieving its vision, strategy and business plan.
  • Responsible for considering key risks and broad based solutions for a number of key projects / issues within company.
  • Engage and facilitate discussions between claims, underwriting and finance departments providing insight into trends emerging from reserving and capital modelling activities
  • Contribute to companys long term strategy and short-term business plan.
  • Contribute to the Business Intelligence strategy and departmental plans.
  • Managing own career by being accountable for ones behaviour, performance and development.
  • Managing junior team members (e.g. Interns) performance to achieve individual and organization goals and objectives.



JOB REQUIREMENTS

  • Bachelors degree (Quantitative Management/Computer Science/Statistics/Applied Statistics/Applied Mathematics or related).
  • Postgraduate degree in the above mentioned fields preferable.
  • 5-8 years practical experience in an analytical/quantitative environment.
  • Insurance knowledge and experience will be an added advantage.
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