A data scientist is the new fashionable role for tech businesses, and they’re in high demand. In the current jobs market, there is increasing competition to hire the best STEM graduates for positions in data science.
As big data becomes an integral part of business operations, more companies need specialist individuals who can use their skillset to accumulate this information from various sources and use it to help reach business goals. But, what exactly is a data scientist, and why should you hire one for your scaling company?
What is a data scientist?
A data scientist is a relatively new breed of analytics expert that has come to light through the rise in big data. They can read and interpret data to solve complex problems but also the curiosity to identify which issues need to be solved in the first place.
A data scientist is part programmer, part statistician and part analyst. They are subject matter experts that can collate a large amount of data and use it to make industry-specific predictions.
What does a data scientist do?
A data scientists’ job is to analyse complex data, but they do much more than that. A data scientist does what software can’t, using their ability to read between the lines. Once they use specific software and coding to get the data out, the possibilities are endless; they can use a whole host of tools and strategies to gain information. A data scientist understands statistical techniques, the tools available to them and how to use the resulting data to a specific business purpose.
They write SQL scripts and gain an understanding of consumer behaviour through various sources of data. Data scientists help with business expansion by improving forecasting and decision making, allowing businesses to act proactively to trends, offer predictions to marketing and other areas of the company as well as providing new perspectives and generating conversations around the data.
What role to data scientists play in HR and recruitment?
In HR, data scientists can use people analytics to influence business and make fact-based hiring decisions. Using people analytics can help with estimating when people are likely to leave the company, average revenue earned per employee, diversity hires, quality of hires and even where to find talent needed to help businesses scale. Data scientists can help businesses of all sizes to manage their recruitment process and succession planning.
There are several opportunities to leverage people analytics across the employee lifecycle from creating fair pay to improving employee retention rates. For example; if you can work out when an employee is likely to leave the business, your leadership team can put in extra effort to retain your top players. Through added benefits, providing new opportunities and making sure they’re happy in their work, you may be able to hold onto the talent you need and reduce recruitment costs.
Data analysis can also help you to identify where talent is. For example, you can identify universities which have graduates in specific areas like robotics and engineering; you can then adjust your recruitment marketing campaigns to target particular institutions and locations.
Which other industries do data scientists work in?
Data Scientists can have a role in almost any business or any industry where there is data to be analysed and opportunities to use it. It depends on a company’s goals and vision, and whether data will help them achieve it.
Tactics like survival analysis or time to event analysis can be applied across multiple industries from engineering (how long will a machine take to break?) to healthcare (measuring life expectancy). Survival analysis focuses on the time until an event happens, which means it can be applied to many different functions; from talent management to saving lives. Similarly, customer segmentation means data scientists can cluster their audience in response to what they’re searching for or buying, allowing them to personalise their pricing or advertising to suit individual groupings. This can apply in recruitment marketing; you can segment your candidates based on their searches and tailor the messaging in your job advertisements to appeal to the right people.
However, here are some of the most common industries that benefit from data scientists.
Healthcare and Pharmaceutical industries use data scientists to improve patient care and manage customer data easily. However, they have other innovative roles in healthcare, such as in Quantified Health, to integrate data with customer wearables and pick up warning signs of illness. Or, to conduct medical imaging to interpret scans and X-rays and identify patterns in data which assist early diagnosis of tumours and diseases.
In the telecommunications industry, big data and data scientists are used to interpret customer behaviours, allowing businesses to develop tailored, customised services and products.
Similarly, Internet businesses from e-commerce to social networks use data scientists to offer personalised recommendations or content to their users based on user behaviour.
In the energy sector, data scientists can be used for everything from discovering alternative energy sources to increasing efficiency and avoiding power shortages and faults. The data used can help these companies to offer better service and avoid mistakes.
In the automotive industry, data scientists can work with artificial intelligence and machine learning professionals to reinvent the industry. Data can be used to create more cost-effective and streamlined production lines, forecast demands, and consumer trends as well as improve the overall quality of products.
Why should you hire a data scientist?
Data is arguably the most valuable resource on the planet. A data scientist helps you to use it properly. Once upon a time, data was just an afterthought to companies, but the internet generation has changed that. Data is now essential information that requires analysis, creative curiosity and skill to create new ways to make money or solve a problem.
Your business and industry will determine which data is most valuable to your growth, but it can include everything from customer behaviour to complex medical scans.
When working for the right business, data scientists have the power to elevate companies to the next level. Data scientists play an integral part in business decision making; they can spot trends and make connections between data that could revolutionise business operations.
When should you consider hiring a data scientist?
A data scientist may not be an ideal hire for startup businesses who are still in the early stages. Hiring a data scientist can be costly, and while you’re still trying to figure out your company’s place in the market, it may not be the most cost-effective hire.
However, when a business is attempting to scale, hiring a data scientist can give a huge competitive advantage. They can help to ensure that fast-growing companies are maximising every possibility and are one step ahead of industry trends and opportunities.
Typically, businesses hire data analysts before scientists, so that the groundwork is already done, and the data is readable. The data scientist can then take it to the next level, and bring all of the data together to the businesses advantage.
What qualities should you look for when hiring a data scientist?
Generally speaking, there are two types of data scientist, the analysts and the creative thinkers. Some data scientists thrive when analysing in-depth data and creating detailed reports which can be passed on to key decision-makers to help a business thrive. Other data scientists prefer to be the driving force behind decisions; using their data-based knowledge and creative thinking to innovate directly. The type of data scientist which could help your business depends entirely on your goals and existing company dynamic.
However, there are some general qualities that you should look out for when hiring a data scientist. Your ideal candidate for a data scientist role has a background in business intelligence, analytics and has experience of making data-driven decisions.
They should have a qualification or background in a STEM subject such as applied maths or computer science. Ideally, candidates for data science roles will understand Python, R, SQL and machine learning.
However, it’s also vital that they can communicate their ideas with the broader team and translate their findings into fundamental business practice. This could be in a written form or verbally depending on the individual you hire and the dynamic of your business; as long as information is communicated clearly and effectively.
Data scientists need to be analytical and be detail orientated as well as have a good understanding of how organisations work. Most importantly, though, they will know your industry well enough to be able to predict future trends and make valuable decisions.
Talent Works has recently been asked to source Data Scientists for scaling tech business, Eagle Genomics. If you’d like our support sourcing a data scientist for your business, then get in touch with our sourcing team today.