Accessibility Links

5 Tips For Data Science Grads

As the sheer volume of data collected by companies increases year on year, so does the demand for professionals who can manipulate, investigate and derive meaning from it. Companies are always looking for new and innovative ways to use technology and data to be more responsive to their customer’s needs.

As a new generation of digital native data science graduate emerges, companies are looking for those who will be the future of their data capabilities.

So with my experience of working with such companies, who are looking for high calibre graduates I know that it is important to maximise your time as a student and gain as much relevant experience and exposure to the right technologies as possible before you start looking for a job.

Here are a few ways for graduates entering the field of Data Science to boost their chances of securing a coveted data science job.

1) Boot camp
Although the most common backgrounds of data scientists can be found in statistics and computer science, many who have specialised in another subject, such as physics or pure maths, for example, choose to participate in courses which can help guide them in the right direction for working in the industry.

There are dozens of boot camps available, including S2DS (Science to Data Science), the ASI post-doctoral fellowship and Metis (based in the US) which all have workshops offering valuable lectures on programming, significant statistical techniques, exposure to technologies like distributed systems; and also offers crucial commercial experience through project work in conjunction with a sponsor company.

2) Competition time with Kaggle
Kaggle is a platform where users can compete in unique challenges run by some of the world's largest companies such as Amazon, Mastercard and Microsoft. Participants are given an opportunity to share their data and predictive models with the data science community. This is a great way to develop programming skills through real world problems with the added bonus of potentially winning cash prizes at the same time!

3) Github
Using GIT, you can write your own packages and tools while gaining exposure to other users' code in Github's extensive library, giving you the ideal starting place to begin developing and debugging through collaboration. This freedom to suggest changes, comment on lines of code and collaborate with programmers from around the world is a powerful and valuable tool.

Using GitHub to hone your skills is a great way to bolster your CV by showing your past work, as well as your contribution to other projects.

4) Online Courses
Whether it is a paid tool such as Coursera or a free site like CodeAcademy, these sites allow you to interactively learn code or how to manipulate data from beginner status through to expert, in areas of R Programming, Applied Machine Learning and Using Hadoop (MapReduce) to name but a few.

5) Be seen is a great place to meet like-minded people, whether it's for code development, help with new languages or even attending industry events with leading scientists. Here in the UK, the Data Science London group has just over 6,000 members meeting regularly and the LondonR seminars provide 3 - 4 short presentations followed by a networking session and drinks.

Overall, there is no singular, defined method of entering into data science, but there are plenty of resources to aid you in continually developing your skill set by exposing yourself to new technology, new people and new ways of thinking. Join the Data and Analytics Network to keep on top of what is going on in the world of data science.

Harvey Gasson
 Harvey Gasson LinkedIn