Senior Data Analyst – IT-Online


  • Diploma in business and quantitative field (econometrics, mathematics, statistics, computer science or similar) Advantageous Post Grad
  • A minimum of 3 to 5 years of relevant experience in data science
  • Application of statistical, mathematical, predictive modeling and forecasting techniques
  • Experience building and implementing supervised and unsupervised machine learning algorithms to solve significant business problems
  • Preparation and presentation of findings to senior management
  • Facilitating discussion and interpretation of results to deepen understanding of the business


Stakeholder management

  • Work with data and analytics teams to identify relevant data sources to perform meaningful customer analytics
  • Work closely with business execution teams to ensure information makes business and financial sense
  • Work collaboratively with various teams to ensure effective achievement of department goals based on analysis results


  • Provide innovative means to support the implementation and effective execution of the strategy
  • Assist in the development and delivery of business cases
  • Use advanced statistical data and methods to generate new business information
  • Cross-reference and correlate the results with supporting documents
  • Make sure that the results of the model are explainable
  • Develop, train, test, implement, update and maintain analytical models
  • Source and prepare data for analysis and modeling
  • Develop dashboards for commercial consumption and interaction of results
  • Implement monitoring mechanisms to measure the business impact of the measures taken against the results and the information provided


  • Ensure solutions adhere to company models, guidelines and standards
  • Operate in project environments and participate in continuous improvement efforts

Delivery management

  • Track and participate in defined working methods including, but not limited to, sprint planning, backlog preparation, retrospectives, demos, and PI planning

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Sean N. Ayres