Data Analyst

2 weeks ago

Cape Town, Western Cape, South Africa Santam Full time

Key Responsibilities:

  • 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
  • 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

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