What will make you successful in this role?

The role requires a candidate with the ability to leverage knowledge of statistical analysis, machine learning, and data modelling to drive business value by providing insights and recommendations based on data analysis.

KEY ACCOUNTABILITIES AND RESPONSIBILITIES WILL INCLUDE:

• Involvement in engagement with stakeholders to understand their business challenges and advise on practical analytics solutions 
• Collaborate with key stakeholders within the data value chain, external and internal, to ensure that the appropriated data sources and data structures are in place for building analytics solutions
• Research, develop and implement appropriate statistical / mathematical / machine learning models as needed
• Keep up-to-date with latest technology trends
• Communicate results and ideas to key decision makers
• To generate and maintain actuarial data assets and make these available to the rest of the organization 
• Develop and maintain outstanding data from the Analytical Base Table and to utilize this to develop predictive models, assist other Business Units in doing diagnostic and descriptive analytics
• Ensure automation of data assets delivered timeously
• Use advanced analytics techniques to solve business problems in cooperation with business units
• Seek out initiatives to enhance Santam’s capability in the Data Science field
• Assist users across the group to make use of the data science workbench

Qualifications and Experience

• B. Degree in Quantitative Management (decision sciences) or Computer Science/Statistics/Applied Statistics/Applied Mathematics (Postgraduate preferable)
• 5-7 years practical experience in an analytical/quantitative environment

Skills

• Strong programming skills ( SQL essential, Python and/or R highly desirable, Spark, Java )
• Experience with common data science toolkits, such as R, Hadoop, Scala, RapidMiner, Alteryx, SAS, SPSS etc. highly desirable
• Experience in Data integration
• Machine learning / Artificial Intelligence and Statistical algorithm development essential 
• Experience with Big Data platforms highly desirable
• Experience in Data management and integration such as Ralph-Kimbal dimensional modelling (Star-schema model) or Bill Inmon Snow-flaking model essential
• Business acumen: Enterprising & commercial thinking: Keeps aware of corporate markets and the state of competitors, identifies business opportunities, views issues in terms of costs, profits, markets and added value.    
• Statistical analysis: Data scientists must have a strong foundation in statistical analysis to effectively identify patterns, trends, and relationships within data.
• Programming: Proficiency in programming languages such as Python and R is essential for data scientists to analyse data and build predictive models.
• Data wrangling: Data scientists must be able to gather, clean, and pre-process data to ensure its accuracy and reliability.
• Machine learning: Knowledge of machine learning algorithms and techniques is necessary to build predictive models and make data-driven decisions.
• Data visualization: Data scientists should have the ability to create clear and effective visualizations to communicate insights and findings to stakeholders.
• Communication
• Problem-solving
• Creativity
• Curiosity
• Financial acumen

Competencies

• Client Focus
• Collaborates
• Cultivates Innovation
• Drives results
• Flexible and adaptable
• IT Data Analysis
• Data Collection
• Advanced analytics to address business requirements
• New technologies and methodologies
• Stakeholder management