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Data science is a field that spans across multiple disciplines, making use of a variety of methods, algorithms and processes often seen in the worlds of science and mathematics. Data sets of various sizes, that is both structured and unstructured, is examined in order to gleam insight that contributes towards larger business issues.

Data Scientists often have an inquisitive nature with the ability to dig deep to understand and define the key drivers for success, even when they may not be clear initially. Often this is achieved by listening to the data and engaging with stakeholders to truly understand the issue at hand. Broad and deep analytic and technical skills, coupled with a creative streak, allowing Data Scientists to identify novel solutions delivering demonstrable value to a subject matter.

Routes into data science often begin with a PhD in a mathematical or science-based discipline. The advanced skills required for these degrees, in areas such as; research, analysis, modelling, hypothesis testing, etc. provide the basic toolkit for a Data Scientist. Other routes include progressing from a data-driven analyst role by up-skilling with the more technical and refined skills that go hand in hand with Data Science.

Recently Machine Learning has become a large focus of Data Scientists by applying Artificial Intelligence (AI) to data management systems. Once programmed, this allows the system to continuously improve itself “by learning” as it processes, instead of being manually programmed. Other responsibilities of a Data Scientist may include:

  • Utilising customer segmentation to provide behavioural insights
  • Predictive modelling to identify the most profitable customers and streamline their journey
  • Shaping the data and analytics strategy
  • Assisting with advanced ad-hoc analyses where required.

Data Scientists usually possess strong technical skills in languages such as Python, R, SQL, & C#.

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