Data Analyst

2 months ago

Cape Town, Western Cape, South Africa Santam Full time
About the Role

Santam Ltd is seeking a highly skilled Data Scientist to join its Group Underwriting division.

Key Responsibilities
  • Collaborate with stakeholders to understand business challenges and provide practical analytics solutions.
  • Develop and implement statistical/mathematical/machine learning models to drive business value.
  • Communicate results and ideas to key decision makers.
  • Generate and maintain actuarial data assets and make them available to the organization.
  • Develop and maintain outstanding data from the Analytical Base Table and utilize it to develop predictive models.
  • 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.
Requirements
  • 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.
  • 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
  • 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

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