In the modern world, we are creating an astounding amount of data per day, and this trend is expected to continue. According to a report by Raconteur, 294 billion emails are sent every day, 65 billion messages are sent over WhatsApp, 95 million photos and videos are shared on Instagram, and 3.5 billion Google searches are happening every day. Even reading these figures it’s hard to visualise the exponential growth of data creation because as soon as this data is collected, it’s out of date. In April 2019 the accumulated digital universe of data was 4.4 zettabytes, and by 2020 that figure is expected to rise by a factor of 10 to 44 zettabytes of data.
This huge explosion in data has led to the boom in the data science industry. Businesses are now under increasing pressure to analyse their data and turn it into actionable insights. You may have heard the phrase “data is the new oil”, it’s punchy, but it’s true. Businesses can make significant improvements in their operations by hiring data scientists and data analysts to interpret their data and unlock its growth potential.
Don’t be left behind
The Figure Eight Data Scientist Report, 2018, found that 29.7% of Data Scientists get contacted for new job opportunities several times a week. 19.3% of the respondents were contacted once a week, and 26.73% were contacted several times a month. Only 3.47% of respondents said they were contacted rarely for new opportunities. This suggests that the demand for data scientists is extremely high, and the supply hasn’t caught up with the demand. Companies that choose to wait, may find themselves struggling to find the best talent.
Data Scientists vs Data Analysts
Data scientists and data analysts fall under the umbrella of business analytics, which has long been a prominent part of business intelligence. A business intelligence consultancy will aim to provide value to an organization by recommending the best talent available to them. It’s common now for a business intelligence consultancy to find themselves under increasing pressure to supply data scientists and analysts to organizations, but what distinguishes the two?
Data analysts and data scientists deal with many of the same tasks but the data scientist takes on a stronger leadership role. A data scientist usually has a strong mathematical background and is comfortable designing and implementing new data solutions to visualise the current state of the business and analyse and advise where improvements can be made. Data analysts tend to work closely with the details in specific parts of the problem-solving activity rather than the big picture, or vision.
According to a 2018 report by MHR Analytics, 80% of UK businesses are planning to hire a data scientist in 2019, and many of these businesses will have done so already. So, what can a company expect when hiring a data scientist?
Data science salary, UK
Data Scientist – £47,509 (Glassdoor)
Data Analyst – £26,232 (Payscale)
Data Analyst salary, London – £32,695 (Glassdoor)
Data Scientist salary, London – £50,585