Discovery Bank Data Scientist Internship 2024

Deadline: Unspecified

The Discovery Bank Data Scientist (Intern) in this role will be using data mining, artificial intelligence, machine learning, and statistical tools to provide insights and analytical results and identify improvement opportunities that would need to be communicated and presented to key stakeholders.  Specifically, in the process and design area of the bank, the data scientist (intern) must support continuous improvement initiatives through quantitative analysis of data related to current business processes and client journeys through the use of process mining tools.  The end objective is to drive the efficiency and effectiveness of complex end-to-end processes by contributing valuable insights for the optimization of the world’s first behavioural bank, Discovery Bank.

Areas of responsibility may include, but are not limited to:

  • Identify appropriate models and algorithms to mine large datasets and develop rich insights into client, process, and performance behaviour.
  • Identify key trends in large datasets using statistical and machine learning techniques to understand the impact of these trends and identify possible actions to take advantage of the trends identified.
  • Analyze, communicate, and present results in a way that provides actionable insights that are practical and interpretable for business stakeholders.
  • Operationalize visual reports and metrics to ensure continuous measurement of critical trends and metrics.
  • Advises on improvement for processes and databases where opportunities arise across the business.


  • Understanding of mathematical and statistical concepts.
  • Technical and coding proficiency (Python, R, SQL, Scala, SAS).
  • Understanding of MS Office.
  • Strong communication skills, both spoken and written.
  • Ability to work with, analyze, and report on data.
  • Knowledge of traditional statistical hypotheses testing and experimenting.
  • Self-driven, motivated, and proactive individual that works well under pressure.

Education and Experience:

  • Bachelor’s degree in either Actuarial Science, Data Science, Statistics, or Mathematics.
  • Honors or a master’s degree would be advantageous.

Click here to apply

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