Data Science Expert

7 days ago

Sandton, South Africa Integrita Group Full time
About the Role

The Integrita Group is seeking an experienced Data Scientist to join our team in Sandton. As a key member of our Data Science and Analytics team, you will play a vital role in creating and enabling data-driven measurement, insights, monitoring, and decision support.

This individual will add value to business areas by providing insights, applying data science to inform and optimise decision making, and building automated predictive and prescriptive analytics solutions that support various business functions and address healthcare challenges.

The role requires involvement in the whole data science development process, including gaining a business understanding, defining the problem, data cleansing and feature engineering, business modelling and simulation, hypothesis generation and testing, machine learning model training, testing and refinement, and finally deployment and monitoring of predicted outcomes within the business solutions.

Key Responsibilities
  1. Identify and test innovative data science techniques that can be utilised in predictive analytics solutions across the Company.
  2. Assist with research on trends in Data Science, specifically for the application in the healthcare industry.
  3. Engage with business stakeholders in the discovery process to identify the business problem/opportunity, elicit requirements, and discuss the expected outcomes of modelling/solutions.
  4. Partner with business stakeholders to define approaches to resolving key business problems and focus on the development of new business strategies.
  5. Assist in developing conceptual designs or models to address business requirements.
  6. Collaborate with subject matter experts to select the relevant sources of data and understand the business requirements to ensure that the models are delivered in an appropriate manner.
  7. Partner with the Data Engineering team to obtain internal and external information and manage data utilisation.
  8. Perform pre-processing of data which includes tasks such as data manipulation, transformation, normalisation, standardisation, visualisation, and features engineering.
  9. Review existing data analytics solutions (code and/or models), measure quality, and identify potential improvements.
  10. Use data profiling and visualisation to understand and explain data characteristics that will inform modelling approaches.
  11. Identify and implement the appropriate data mining/statistics/machine learning techniques.
  12. Implement predictive models on large datasets (including distributed parallel computation platforms such as Spark).
  13. Perform business modelling that translates decisions and business processes into a computational model.
  14. Validate and test analysis/models using appropriate techniques (back testing, A/B testing, scenario modelling, etc.).
  15. Implement models using Company standard processes and techniques.
  16. Monitor and maintain models with specific focus on model performance and the results being fit for purpose.
  17. Ensure full compliance to statutory regulations, policies, procedures, best practice, and professional standards in line with the Company strategy.
  18. Review and update all policies relating to data science.
  19. Communicate findings to business with various skill levels and in various roles, presenting trends, correlations, and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights and defends recommendations.
  20. Generate concise reports with relevant visualisations and commentary for management.

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