Look at any list of most desired and sought-after tech roles and in the top positions you’re going to come across the title ‘Data Scientist'. Demand for data experts remains buoyant globally, which isn’t surprising given the vast volumes of data that businesses need to analyse and interpret.
LinkedIn ranked the role of the data scientist as the most promising job in the US of 2019 and according to a Royal Society report (2019) demand for data scientists and data engineers has more than tripled over the past five years. According to ITJobsWatch, the median salary for a data scientist in the UK (six months to February 2020) was £62,500.
Most of the work data scientists do is in contributing to systems that provide decision support. Therefore, experience of supervised machine learning, both classification and regression, is what most organisations are after. Candidates will also be expected to be proficient in key programming languages such as Python, R and SQL. Increasingly, the world is moving to the Cloud and as such a working knowledge of any of the main providers, such as GCP, AWS or Azure will be very beneficial for candidates.
To learn more about the work data scientists do and the skills companies are looking for, we spoke to Dr. Paul van Loon, CFA, Head of Analytics at Forecast, a data and analytics consultancy with its HQ in Edinburgh and offices in Sydney and Toronto.
We learn that data science isn’t a new discipline, “A lot of people are keen to jump on the data science bandwagon but a lot of what is now called data science, people have been doing for many years. Previously this would have fallen under the umbrella of econometrics, operational research, statistics and predictive modelling.”
‘No quick or easy path’
So what kind of skills do data scientists need to succeed? Organisations will typically require most candidates to have a computer science, mathematics, physics or statistics background.
A solid understanding of statistics is paramount, according to van Loon. “There’s a danger in everyone wanting to be called a data scientist, and companies wanting to attract candidates with that title. It’s not enough to simply follow a set of online courses – those are great for upskilling and building on what you already know. There is no quick or easy path to becoming a data scientist, there is no substitute for building models.”
For organisations such as Forecast, potential recruits need far more than first class technical skills. “We look at the attitude of the individual, as we want proactive, confident people who not only deliver high quality output, but are comfortable interacting with stakeholders.”
The overriding message for data scientists is that there are no shortcuts to success. To develop your career in one of the hottest tech disciplines, you need to have a good grasp of the technical fundamentals combined with a proactive, ‘can do’ attitude.
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