When Should You Hire a Data Scientist for Your Business?
Posted on: 19 Oct 2017
As a fast-growing business, you want to make the most of every marketing opportunity available. And big data is one of the biggest opportunities out there.
But big data needs deep data divers. Those data scientists with the skills to plumb the depths and come back up with a gleaming pearl of information. If you’re thinking about expanding your marketing team with one of these sought-after roles, there are a few things you need to consider to get a good return on your investment. We explain what you need to have in place before hiring.
Immense Information Requires Special Skills
Big data was the next big thing to help marketing realise its full potential. But as data poured in from multiple sources in different formats, incomplete and formless, it soon became apparent that a special skill set was required to tame the data and get something useful from it.
Rather than developing periodic reports that summarise historical activity, businesses want an on-going conversation with the data. Gaps need to be filled and data cleansed, analysed and interrogated to generate forward-looking insight and solutions.
The role of data scientist sprang up in marketing teams.
What They Bring
Different to other data analysis roles, data scientists deliver process optimisation, bring a new perspective to market segmentation and have the in-depth data and statistical analysis skills to uncover new insights and novel solutions. All with a customer-focussed bias.
While they can hack data and write code, they are also able to translate findings into understandable outcomes for colleagues, often presenting information creatively and visually. This unusual blend of skills is not always easy to recruit for.
They are also intensely curious and want to dive beneath the surface of the data and only come up for air with hypotheses to test.
What You Need in Place
Unless you have huge data sets in place, your data scientist has nothing to work with. They need to be in a position to analyse enormous data sets with the potential to reveal process or product solutions. With only a small product range or data set, the opportunities are limited and could potentially be performed by someone with a different skill set for a lower salary. Put a data scientist in a position where they can’t be effective and they’re likely to become bored and leave.If you do find that you have significant amounts of data that creates more questions than it solves and no obvious solutions, a data scientist could be the answer. But don’t jump in just yet – there are some more things you need to have in place too.
If you want to access data or provide regular historical reporting – like quarterly sales figures – you’re not ready for a data scientist. In this case, a data analyst would be a better hire. They can provide the information your business needs and set up and maintain data warehousing services to accommodate huge data sets.
Source: Data Scientist Insights
To be ready for a data scientist, you need to be in a position where your business is crying out for predictive analysis. Someone who can perform statistical interpretation, build, deploy and test predictive models, and build powerful recommendation engines. With a data analyst already in place, they will have laid the groundwork for a data scientist who will rely on warehoused data to be able to perform their role effectively.
Bring them in too soon and their skill set will be wasted. As will some of the money you’ll be paying for their wages.
Struggling Software Engineers
If your software engineers are deciding how an app will operate they’re likely doing this on a best guess basis. Choosing where adverts will be displayed, what buttons and menus look like and where to place inventory can be better decided by a data scientist. They will:
● interrogate large data sets through a marketing lens
● run optimisation analysis
● predict best performance
● propose more effective solutions
By interrogating different approaches to ad placement, effectiveness and performance data they will be able to deliver the most optimised page.
A Culture of Experimentation
Data scientists are insatiably curious. They don’t just want to be a consultant – they want to fashion their own tools and conduct academic-style research at the cutting edge of the field.
Be prepared to manage people in these roles by giving them room to grow and allowing them to build new data tools and solutions that will leave a lasting footprint. Be prepared to include them in the thick of the issues as they develop to provide real-time business solutions. This means giving them access to people in charge of products and services. Quick decision-making will allow them to test hypotheses and roll out solutions to customer-facing products and processes. This will enhance your offering and generate return on investment.
A Specialist Recruitment Partner
As the Harvard Business Review recognised back in 2014, data science is the new ‘sexy’ role on the block. Tipped to earn more than lawyers and doctors in the USA, these roles will command big money due to the scarcity of suitable candidates.
Universities tend not to have data science courses, and with STEM subject graduates in short supply, good data scientists will have many open doors to walk through; including big consulting firms who are still trying to amass people with these skills.
Catching up with the rest of the market can make recruitment tricky. When the time’s right to recruit, work with a specialist marketing recruitment partner to deliver the right candidate for your business from their pool of suitable candidates.