SALARY – MARKET RELATED
Division – Data Management and Analytics Division
Reporting to: Data Science And Analytics Manager
The Senior 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 optimise decision making and build automated prescriptive analytics solutions that support various business functions and address healthcare challenges.
The role requires involvement in the whole data science development process of 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.
- Identify and test innovative data science techniques that can be utilised in predictive analytics solutions across the company.
- Assist with research on trends in Data Science, specifically for the application in the healthcare industry.
- Engage with business stakeholders in the discovery process to identify the business problem/opportunity, elicit requirements and discuss the expected outcomes of modelling/solutions.
- Partner with business stakeholders to define approaches to resolving key business problems and focus on the development of new business strategies.
- Assist in developing conceptual designs or models to address business requirements.
- 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.
- Partner with the Data Engineering team to obtain internal and external information and manage data utilisation.
- Perform pre-processing of data which includes tasks such as data manipulation, transformation, normalisation, standardisation, visualisation and features engineering.
- Review existing data analytics solutions (code and/or models), measure quality and identify potential improvements
- Use data profiling and visualisation to understand and explain data characteristics that will inform modelling approaches.
- Identify and implement the appropriate data mining/statistics/machine learning techniques.
- Implement predictive models on large datasets (including distributed parallel computation platforms such as spark).
- Perform business modelling that translate decisions and business processes into a computational model.
- Validate and test analysis/models using appropriate techniques (back testing, A/B testing, scenario modelling, etc.).
- Implement models using standard processes and techniques.
- Monitor and maintain models with specific focus on model performance and the results being fit for purpose.
- Ensure full compliance to statutory regulations, policies, procedures, best practice, and professional standards and is in line with the company strategy.
- Review and update all policies relating to data science.
- 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.
- Generate concise reports with relevant visualisations and commentary for management.
- Degree (Honours, Masters or PHD) in Statistics, Computer Science, Engineering,Mathematics and / or a combination of these.
- Relevant data science certifications such as Python, Microsoft, AWS, Hadoop, big data, machine learning, cloud infrastructure
- A minimum of 6 years’ experience in data science related projects.
- 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.
- Experience with SQL and working with large-scale data sets.
- Knowledge and practical experience applying machine learning techniques.
- Experience working in agile development teams.
- Experience in operationalising data science solutions or similar product development.
- Experience in a high-scale production environment is critical.
- Provide support to the ever evolving company strategy of person centred health and care and the digitisation strategy. Continuously deepen the awareness of the strategy to address new challenges within the Healthcare sector, to build a competitive advantage and sustainability through the company moat strategy.
- Knowledge and understanding of the Data Science Development Cycle: business understanding, data profiling, feature derivation and selection, data modelling, model evaluation, productionisation, monitoring.
- Outstanding problem solving and analytical skills.
- Knowledge of how the business functions and the underlying strategy which supports the business model as well as improving clinical health and care.
- The ability to build, analyse and interpret numerical and non-numerical data to determine potential statistical inferences to inform business and clinical decisions.
- Ability in applying statistical machine learning techniques to predictive modelling problems and translating this into business solutions.
- Ability to clean and unify messy and complex data sets for easy access and analysis. Combining structured and unstructured data.
- Ability to provide detailed explanations (visually and verbally), representing information in the form of a chart, diagram, picture, using tools such as Kibana, Tableau, Power BI, etc.
- Write programming code (python / java) based on a prepared design.
- Understand leading edge technologies and best practice around Big Data, platforms and distributed data processing i.e. Hadoop ecosystem (distributed computational power)-HDFS/Spark/Kafka.
- Ability to conceptualise and frame a problem, develop hypothesis and identify objective measures to estimate accuracy of machine learning/statistical processes and perform testing and validation with careful experiments.
- Understanding of data flows, ETL and processing of structured and unstructured data within the data architecture.
- Comprehensive solution design based on a good understanding of the Big Data Architecture.
- Strong Business and clinical knowledge that will contribute to exposing patterns and an aptitude to understanding how the business functions and the underlying strategy which supports the business model as well as improving clinical health and care.
- Knowledge of health-related policies, procedures and legislation.
Please Note – If you do not receive feedback within 3 Months, please consider your application as unsuccessful.
- data scientist
- data analytics
- development business solutions
- engage with stakeholders
- python language
- microsoft azure
- experience in data science
- acturial analyst with data science experience
- microsoft azure certification
- amazon web services
Desired Work Experience:
- 2 to 5 years Clinic & Hospital
- 5 to 10 years Data Analysis / Data Warehousing
Desired Qualification Level:
About The Employer:
Employer & Job Benefits:
- Medical Aid
- Provident Fund