Genetic research is opening the door to possibilities beyond our comprehension – personalised medicine, preventative treatment and even the complete eradication of hereditary conditions. But while scientists are busy collecting all the information they need to do these incredible things, to truly make these wonders of modern medicine a reality, the life sciences industry desperately needs to recruit hundreds, if not thousands, more data scientists. Here, we look at why computational scientists and mathematicians could hold the key to humankind’s greatest achievement:
Science and technology are intrinsically linked, as developments in one field perpetuates advances in the other. This is aptly demonstrated in the study of Genomics, where advanced technology is helping research scientists to map and analyse DNA in a way not thought possible even 10 years ago.
Genomics studies are effectively giving us the tools to discover how our genetic make-up is susceptible to different diseases and how gene therapy may be able to give us a healthier future, but to do this effectively, scientists need to make sense of all the data they are collecting. And when you consider that one person’s genome generates 200GB of data, comparative studies of multiple genomes suddenly becomes an impossible task for biologists.
This is where the need is greatest for people with mathematics, statistics, computer programming and data analysis backgrounds. Without their help to decode the information and look for patterns and variances, it is incredibly difficult to find the answers scientists need to turn genetic evidence into useful information for future drug targets or clinical decision-making.
There is also a big margin for error when appropriate statistical methodology is not applied to big data. This means that potentially scientists can embark on a wild goose chase based on a coincidental pattern, plunging time and resources into projects which will not bear fruit.
So, to help the life sciences sector make proper use of its big data, the industry needs to recruit ‘computational’ scientists – and fast. According to statistics, global demand for data scientists will exceed supply by more than 50 percent by 2018.
The picture is the same in the UK, where there are simply not enough appropriately skilled people working in the life sciences industry, or coming through the ranks at university, to fill these vacancies. That’s why the net is being cast wider to look for candidates in other industries who have transferrable skills.
The good thing about computational scientist roles (sometimes called data scientists or statistical geneticists) is that you don’t need to have a life sciences degree to get a foot in the door. Many candidates come into the industry with qualifications and experience as computer scientists and simply transfer their skills to biology.
One of the most unlikely sources of data scientists with the necessary skills set for a life sciences role is actually the online gambling industry, where human and risk factors come into play. The advertising and banking sectors also have appropriately skilled professionals, as their work relies on dealing with big data, its visualisation and analysis. All of these commercial data science roles use the tools, algorithms and concepts needed for genomics so applying them to scientific data is not a huge leap.
Remuneration packages in the life sciences are competitive, although this will depend on where you are working (Government or privately funded research institute, big pharma company, small biotech start up etc) and may not be quite as extravagant as those offered in comparative commercial roles.
The one thing that can be said of genomics roles though, is that data and computing has such a pivotal part to play in new medical breakthroughs, that it is an exciting and rewarding career choice which is contributing to research that could change the world. You can’t say that about online bingo.
If you are a computer or data whizz looking for a more fulfilling career, contact the team at Paramount to see whether your next move could be into the life sciences sector.