Data Scientist

1 week ago

Sandton, South Africa Dimension Data Full time

The role will primarily work with cross functional teams across data analytics, actuarial analytics, data science, clinical (coders and doctors), and data engineers in an international team. The objective of the role is to ensure timeous, robust and accurate delivery of relevant data science methods including responsibility of research, development, and monitoring of models. Effective communication between a range of stakeholders is vital to ensure delivery.

**Requirements
- Develop data science models fit for purpose to solve business problems
- Rapidly test and iterate different data science algorithms
- Ownership of model monitoring statistics and trigger points to decide model retraining parameters.
- Contribute into the MLOps process to successful productionize models with MLOps Engineers
- Mining large structured and unstructured datasets for a multitude of companies with different data structures
- Usage of data science to find new insights to inform healthcare strategies and develop product, there will be a broad range of products to understand from clinical, operations, financial, fraud, digital, sales and marketing, wellness, etc.
- Performing basic data analytics ad hoc to extract core data insights
- Present data and model findings in a way that provides actionable insights
- Connecting with a multitude of local and international stakeholders to understand the data, systems, and analytical processes in a healthcare context
- Improve processes and data outcomes where opportunities arise

**Qualifications
- Degree in either Data Science, Statistics, Applied Mathematics or Computer Science
- Experience in healthcare data science is preferred
- Proficient in SQL, python, and advanced excel
- Proficient in exploratory data analysis for data science
- Proficient in a range of data science algorithms (Machine Learning, Deep Learning, Reinforcement Learning, etc.). Specialisation in one field is also welcomed.
- Working experience in the MLOps process and AI governance
- Working experience in health outcome indices and metrics and measures
- Working experience of the model lifecycle in at least 2 out of the following areas of expertise from clinical, operations, financial, fraud, digital, sales and marketing, wellness, or any relevant dataset in healthcare
- Knowledge of patient health management, provider profiling, healthcare reporting, and other key healthcare technologies etc. is advantageous
- Knowledge of clinical tools including coders, groupers, and classifications is advantageous
- Knowledge of data science in the healthcare space is advantageous
- Knowledge of healthcare benefit pricing, product pricing and other actuarial calculations (reserving, risk rating, etc.) is advantageous
- Experience in Microsoft Azure preferred (Databricks, Synapse, Data Factory, etc.)

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