Bioinformatic research generates a huge amount of data, and making sense of it requires the expertise of people who have the right computer and mathematical skills to process the information. Data science jobs don’t really require too much life sciences experience, but they do require a strong academic background in data, computer science and/or maths.
Genomics research generates a huge amount of data and making sense of it requires the expertise of people who have the right computer and mathematical skills to process the information. The most sought-after candidates in the field of bioinformatics are data scientists.
A data scientist brings together large amounts of information, sometimes from different sources, and finds the best way of sorting it for analysis using algorithms and statistical methodology such as the Random Forest or Markov Models. The process can sometimes involve applying machine learning, artificial intelligence (AI) and deep learning to help read the trends and patterns within the data.
The data scientist role is incredibly important as it is used to identify therapeutic areas and targets for drug discovery using biological and chemical data. The information the data scientist is able to collate and analyse eclipses previous drug target selection processes and can help to bring more effective treatments to clinical trial, reduce the number of failures at trial and establish a higher chance of success. For pharma companies, working in this way can save them £500m on the cost of bringing a drug to market and reduce the clinical trials phase by five years!
While data scientist jobs don’t really require too much life sciences experience, they do require a strong academic background in data, computer science and/or maths. A proficiency in programming is also an essential part of the role – either R or Python would be ideal.
Data science candidates for the pharma industry can come from a diverse range of backgrounds and work experiences. Believe it or not, external data scientists with the necessary skills set for a similar role in life sciences come from advertising or the online gambling sector, where human and risk factors come into play. Data scientists are also in demand in genomics research, where large volumes of genomic data requires comparison and analysis.
Under the wider umbrella of data scientist roles, there are a number of other jobs which require data science skills and experience – for example data wrangler and data curator. A data wrangler (yes, it’s a real thing) herds the relevant information and biomarkers from the bioinformatics scientific research so that an analyst can make sense of the data.
A data curator pulls together information from a number of different sources so that they can be combined and studied together. Data curation roles could be based at research organisations or pharma companies, so there is lots of avenues to explore.
Data scientist salaries start at £40,000 for an entry level role, and move up to £90,000 for more senior positions.
If this sounds like you, it’s a great time to make the jump into a Data Scientist career, as globally, demand for data scientists is projected to exceed supply by more than 50 percent this year. This skills shortage means that opportunities to move on up are plentiful for data scientists and unlike some professions, your skills will be transferrable to other industries.
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