Data Science & Big Data Analytics Recruitment

Whilst continuing my personal studies around the subject of Data Science & Big Data Analytics and more importantly, sponsoring and attending several conferences. It is clear that unlike many generic “IT” vacancies, consultants seeking work in this space are not only motivated by money and management potential. This was also compounded by an article I read which in short, flagged up the following:-

“Many people dream of working as a data scientist at a great company such as Google or Facebook, bringing home a good salary, and enjoying the perks of a thriving, employee-centric firm; however, there's more to life than a nice salary and an onsite barbershop. If you go into data science just for the perks, that's a huge mistake. To be a successful data scientist, you need to love data science.

Data scientists love to solve problems, write code, build charts and graphs, and work all night with others who love the same things. I'm not saying you should live to work, though work-life balance becomes a lot easier if you enjoy what you do. For good data scientists, it's not just a job, it's a state of mind -- they believe they were born to do their job, and they feel fortunate they can make a good living at it.

As a leader or a manager, it's important to hire the right people for the data scientist position. Some people may already have a sense they're not right for data science, and others may have a false sense of optimism. Either way, it's your responsibility to protect your organization and your interviewee from an improper fit.” 

I take pride in what I do and I am very passionate in this space. I have been working closely with Rackspace in the States and a number of other company’s where I was approached to facilitate several seminars on opportunities in the UK, EMEA & APAC for strong post-grads with aspirations to get into Data Science & Big Data Analytics. As a result, I feel well positioned to assist with any clients or candidates who are looking to get into the Data Science & Big Data Analytics space.

It’s not an easy task, but try me I do love a challenge.