Data Scientist

A Data Scientist can also be known as a Quantitative Analyst, Advanced Analyst or Financial Engineer. The Data Scientist is a mathematician, a statistician, a computer scientist and a trend-spotter. Their models are used by organisations to make decisions about risk management, investment and pricing. They capture and analyse new sources of data, build predictive models and run live simulations of market events.

A Data Scientist can also be known as a Quantitative Analyst, Advanced Analyst or Financial Engineer. The Data Scientist is a mathematician, a statistician, a computer scientist and a trend-spotter. Their models are used by organisations to make decisions about risk management, investment and pricing. They capture and analyse new sources of data, build predictive models and run live simulations of market events.

Data Science is an inter-disciplinary field, drawing on scientific methods, mathematical and computer tools as well as financial theory. Data scientists use these skills to develop complex mathematical and computer models, and implement processes and systems to draw knowledge and insights from large sets of data. The field includes data mining, big data analysis, machine learning and artificial intelligence.

Business Analysts range from R300-R470 000.

Data Scientists turn floods of data into valuable and actionable information using algorithms and machine learning, along with their own skills in maths, statistics and programming. Once raw data has been turned into information, data scientists use their industry knowledge, contextual understanding, and their ability to question existing assumptions, norms and ways of working, to present new solutions to business challenges.

They take on projects to meet customer or business needs and present their results using clear and engaging language. As such, a data scientist needs an understanding of communications and the ability to translate complicated learnings into a format that is easily understood. You will be responsible for presenting your findings to management, or to clients, in a way that makes sense to them.

Your insights will be used to create new plans and processes, and it will be your job to ensure that these plans are workable and implemented correctly

As a Data Scientist, you are most likely to work in an office-based corporate environment, in wide variety of industries. You will work largely under your own guidance, and will be responsible for your own decision making, deadlines and work delivery. You may be required to oversee a team, and to establish networks across the organisation you work for. It is a self-driven field with a high level of accountability, long hours and a need for creative thinking and focus. You will need to continually upskill yourself and stay on top of trends. Typically, a data scientist can earn between R20 000 and R64 000 a month

  • Data Scientist
  • Quantitative Analyst
  • Pricing Analyst
  • Econometrician
  • Financial Engineer

The Data Scientist will require a Masters or Honours degree in any of the below fields. Undergrads are seldom hired.

  • MSc Data Science
  • MSc Business Analytics
  • MSc Data Science and Analytics
  • MIT (Big Data Science)
  • MSc Physics
  • MSc Statistics
  • MSc Applied Mathematics
  • MSc Industrial Mathematics
  • MSc Actuarial Science
  • MSc Operational Research
  • MSc Engineering
  • MSc Numerical Mathematics

  • Nelson Mandela University
  • North-West University
  • Rhodes University
  • University of Cape Town
  • University of Johannesburg
  • University of KwaZulu-Natal
  • University of Pretoria
  • University of Stellenbosch
  • University of the Western Cape
  • University of the Witwatersrand

These degrees are geared towards developing analytical, mathematical and science skills, all of which are vital in this field.

Mathematical skills to develop include calculus (including differential, integral and stochastic), linear algebra and differential equations, numerical linear algebra (or NLA), probability and statistics, neural networks, and game theory.

Computer skills are geared towards data gathering, data modelling, analysis and presentation. Knowledge required includes C++, Python, R, Scala, SQL basics, Java, .NET, VBA Macros, Excel, MatLab, SAS, S-PLUS/R (used for statistical analysis), object-oriented programming, distributed computing like Spark and cloud data storage and computing.

Financial knowledge is no less important, and you will need to develop your knowledge of financial modelling, portfolio theory, accounting principles, financial statement analysis, knowledge of credit risk-products, equity & interest rate derivatives, fixed income and finally, systematic and discretionary trading practices.

You will also need an ability to communicate complicated ideas to people who do not necessarily have your knowledge base. A data scientist needs an excellent command over English and strong conversational skills. It also requires the ability to present findings in easy-to-consume reports and presentations.