Data Scientist - Medical Sector (Sandton) R60 000 – R66 000 Pm Ctc

Data Scientist

The Data Scientist will support the Data Science and Analytics team 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 optimize 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 modeling 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.

Duties & Responsibilities

1. Identify and test innovative data science techniques that can be utilized in predictive analytics solutions across the Company.
2. Assist with research on trends in Data Science, specifically for application in the healthcare industry.
3. Engage with business stakeholders in the discovery process to identify the business problem/opportunity, elicit requirements, and discuss expected outcomes of modeling/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 relevant sources of data and understand business requirements to ensure that models are delivered appropriately.
7. Partner with the Data Engineering team to obtain internal and external information and manage data utilization.
8. Perform pre-processing of data, including data manipulation, transformation, normalization, standardization, visualization, and feature engineering.
9. Review existing data analytics solutions (code and/or models), measure quality, and identify potential improvements.
10. Use data profiling and visualization to understand and explain data characteristics that will inform modeling approaches.
11. Identify and implement 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 modeling 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 modeling, etc.).
15. Implement models using Company standard processes and techniques.
16. Monitor and maintain models with specific focus on model performance and results being fit for purpose.
17. Ensure full compliance with statutory regulations, policies, procedures, best practices, 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 clear and concise manner.
20. Generate concise reports with relevant visualizations and commentary for management.

Desired Experience & Qualification

1. Education: Degree (Honours, Masters, or PhD) in Statistics, Computer Science, Engineering, Mathematics, and/or a combination of these.
2. Relevant data science certifications such as Python, Microsoft, AWS, Hadoop, big data, machine learning, cloud infrastructure.
3. A minimum of 5-6 years' experience in data science-related projects.
4. Experience with Python/Microsoft ML and tools available within the machine learning ecosystem (i.e., NumPy, Pandas, Matplotlib, SciPy stack) and working in Jupyter notebooks.
5. Experience with SQL and working with large-scale datasets.
6. Knowledge and practical experience applying machine learning techniques.
7. Experience working in agile development teams.
8. Experience in operationalizing data science solutions or similar product development.
9. Experience in a high-scale production environment is critical.

Package & Remuneration

R60, – R66, pm CTC. Medical aid + Pension included.