REPORTS TO: General Manager – Business Analytics and Risks Management
OverView: The position requires broad analytical and statistical skills to mitigate potential risk factors that involve healthcare stakeholders and their associated business models. Such risk factors include demographical, morbidity shifts, medicine cost inflation and utilisation changes as it relates to but is not limited to Fraud waste and abuse identification and risk mitigation and predicative analytics. After analysing these factors, decisions, suggestions and implementation of solutions on how to safeguard these organizations against identified risks, and results reported back to the stakeholders.
RESPONSIBILITIES/ KEY PERFORMANCE AREAS:
MODELING DESIGN, DEVELOPMENT AND IMPLEMENTATION
Work with the respective stakeholders to deliver the required capability which involves the following aspects:
- Analysis of the requirements
- Identify valuable data sources and automate collection processes
- Undertake preprocessing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms
- Combine models through ensemble modeling
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Collaborate with engineering and product development teams
- Design to ensure a flexible and automated solution
- Testing of the solution with required feedback to the developer ensuring delivery to requirements at the required quality
- Implementation and training to the respective team members & Clients as applicable
- Documentation management as appropriate
- Statistical and financial modeling
- Risk identification and mitigation as it relates to but not limited to Fraud waste and abuse.
- Clinical predictor analytics as it relates to medical risk factors and early detection of possible chronic illnesses and/or hospital event predication based on clinical and or utilization protocols to be used in creating machine learning/AI models.
DATA WAREHOUSE DESIGN
- Form part of the data warehouse design team with the Business Analytics analyst, General Manager, ETL data warehouse specialist(s) wrt projects /products as identified
- Solution Analysis and underlying procedures, database design and logic.
BI PRODUCT DEVELOPMENT AND ENHANCEMENT
- With the BI Systems Analyst form part of the BI product design team consulting stakeholders with regards to technical & statistical view of product development for identifying and mitigation of business risk.
- Demonstrate modeling capability/functionality to stakeholders.
- Identify and implement mitigation strategies as it relates to business and industry risks.
CONSULTING/MENTORING ROLE
- Consult, mentor and train various members in the BI department with regards to coding / reporting involving the following
- Financial field application & financial calculations
- Financial modeling applications
- Application of Statistical/Actuarial methodologies
- Application of Machine learning / AI methodologies
- Fraud waste and Abuse methodologies
EDUCATIONAL REQUIREMENTS:
- Tertiary qualification e.g. B.Sc/B.Com Actuarial Science or Financial Mathematics or Mathematical Statistics
- Machine learning/Operations research/AI applications
- BI experience
- Qlik suite of tools essential / Cognos experience will be beneficial
BACKGROUND EXPERIENCE & TECHNICAL SKILL REQUIREMENTS:
Analytics – a min of 5 years’ experience:
- Data Modelling
- Statistical trend and correlation Analysis
- Outlier identification
- Report writing
- Automation solutions
- Neural Network experience will be beneficial.
- Fraud, Waste and abuse experience as it relates to healthcare will be beneficial.
- Proven experience as a Data Scientist or Data Analyst
- Experience in data mining
- Understanding of machine-learning and operations research
- Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset
- Experience using business intelligence tools (e.g. Qlikview, Cognos) and data frameworks (e.g. Hadoop)
- Analytical mind and business acumen
- Strong math skills (e.g. statistics, algebra)
- Problem-solving aptitude
- Excellent communication and presentation skills
The following technical skills
- Microsoft SQL Server 2019 SSIS, including active X-scripting (VB script)
- Microsoft SQL Server 2019 Transact-SQL & stored procedures
- Understanding Ralph Kimball Data Warehouse star schema methodology
Desired Skills:
- Artificial intelligence
- Python
- Machine learning
- Cognos
- Data Modelling
Employer & Job Benefits:
- Pension Fund
- Medical Aid
- Annual Bonus