Essential Data Science Roles in Life Sciences for 2024

5 Minutes

The life science market is experiencing rapid growth, with AI in life science expected to achieve an annual growth rate of 20% (CAGR) by 2027 (since 2020), predominantly the result of increased adoption of data-driven technologies and significant private and public investment.

We’re seeing a shift towards diagnostics and medical devices with a huge increase in job opportunities in this market, as a result of the pressing focus and investment in diagnostic and preventative tools.

Why are data driven roles more prevalent in life science?

More and more data driven roles are becoming increasingly sought after across the life science industry and this is set to continue growing rapidly in the coming years, Nathan Tambini, Senior Business Consultant at CSG Talent specialises in data focused roles within the life science industry and notes the increase in data led roles throughout the industry; "Data driven roles are prevalent in life science due to the complex nature of biological systems and the importance to analyse large amounts of data to progress and advance personalised medicine, drug discovery and regulatory compliance. This has resulted in rapid growth across all areas within the data field."

Here we delve into some of the core reasons why we are experiencing increase in the prevalence of data driven roles in life science:

Drug development and discovery

As a result of the increase of vast amounts of data and data analysis capabilities, we are seeing more patterns and trends identified by researchers which leads to an increase in knowledge about diseases, potential treatments, and new discoveries. This process is much more efficient and leads to more successful drug development in comparison to older research practices which took more time with experimentation.

Huge data growth

Through various sources, the life science and diagnostics industry creates large volumes of data including clinical trials, genetic information, sensor data, imaging and medical records.  This data and data driven insights allows life science professionals to enhance and inform their decision making more effectively.

Decision making driven by data

With increased data because of new technologies with life science, the industry now presents a large volume of data to be analysed and managed. Life science and diagnostic businesses are crying out for skilled talent to interpret this data and enable the technology to have the desired results on diagnostics, care and patient outcomes.

Personalised medicine

Through the application of intelligent data analytics, the genetic makeup of patients can be analysed to create personalised treatment plans for individuals, also based on their medical history. With this high-level insight and reliable data to base treatment on, we are seeing greater patient outcomes with reports of reduced side effects of treatments.

Eight data driven roles in life science most in demand this year

While individual business needs will vary and determine the types of roles your business will need to move forward, there are core data driven roles within life sciences that all organisations should consider hiring in the short term or long term.

The rapid rise in data and digital technology application within life science has resulted in the increased demand for highly skilled, data driven roles. In this article, we explore some of the life science industry’s most popular and rising demand data driven jobs.

Data Scientist

A Data Scientist is responsible for identifying data trends and patterns to solve complex problems an develop data-driven solutions. Data Scientists use statistics and machine learning to establish insights from huge data sets to enable them to identify significant trends.  As a result, this role within a business has a significant impact on improving products, processes and potential treatments developed.

Data Engineer

Data Engineers build and manage the infrastructure to enable the delivery of data, their work ensures there are pipelines in place to collate, clean and transform data and is a crucial role in data analysis. As part of the process, Data Engineers ensure the data is of high quality, accessible and secure.

Healthcare Data Analyst

The role of Healthcare Data Analyst is to identify trends and patterns through the analysis of clinical trial data and medical records. With this data insight, there can be a significant impact on patient care outcomes and healthcare operations.

Software Engineer

A Software Engineer will work in close collaboration with all other data-driven roles within a business to design and develop software applications. A part of the role will be to also test the effectiveness of new software through data analysis.

Machine Learning Engineer

Responsible for building machine learning models for use within the life science industry is a Machine Learning Engineer. A Machine Learning Engineer has strong expertise in programming languages, machine learning algorithms and cloud computing, working on projects involving medical image analysis, drug discovery and patient risk management.

Eloise Hadley, Senior Consultant in Life Science Recruitment at CSG Talent works closely with businesses to attract Machine Learning Engineers who are increasingly in demand this year - "AI is drastically changing all areas in healthcare; its emergence is driving many forces in hiring trends over the course of 2024. The development of AI requires different areas of specialisations, with ML engineers being forefront of developing new AI systems in data."

Data Architect

Data Architects have oversight on all data architecture across a business, including design, implementation, and management. Data Architects are responsible for decisions on how data is stored and accessed, ensuring all data is secure and compliant.

Computational Biologist

A Computational Biologist works across systems biology, proteomics and genomics predominantly, applying computational techniques to successfully interpret and analyse large volumes of data.

Bioinformatics Scientist

A Bioinformatics Scientist plays a key role in the discovery of new drugs, genomic research and personalised medicine, utilising computer science to review and analyse large volumes of biological data. Teams of Bioinformatics Scientists develop algorithms to successfully manage and interpret the biological and genomic data.

As data focused roles and teams begin to evolve and grow within an organisation, we’re noticing an increase of senior level leadership positions across each function including Directors and Vice Presidents of Data Scientist, Software, Machine Learning and Bioinformatics. We’re also seeing demand for specific skillsets across the life science industry, some of which include; the ability to collaborate and communicate effectively to both internal and external stakeholders, dealing with complex data sets and conversations, professionals within life sciences need to be able to articulate clearly and confidently.

With many roles now being led by data, strong analytical and interpretation skills are vital for those working within the field to be able to establish meaningful insights and actions. Life science professionals encounter challenge and obstacles where it’s crucial to find solutions, alternative approaches and innovative ideas, therefore problem solving, and critical thinking skills are highly sought after in this field.

Working with an Expert Life Sciences Recruiter

At CSG Talent we support organisations within life sciences, diagnostics, personalised medicine, data AI, biotech AI and machine learning. Our expert team hire talent for business-critical data driven roles, keeping up with the demand of digital transformation in the market. Our expert team have experience in niche areas within the life science market and recruit for roles across all business functions at a senior level, supporting large corporations to start-ups across the globe.

Irfan Bhatti, Business Consultant in Life Science at CSG Talent emphasizes how beneficial and important a large network of data professionals is to him as an expert life science recruiter, and the clients he supports with hiring strategies - "With the widespread adoption of AI and data roles within the Life Science market, having a strong network of data driven professionals to address this has never been more important. This brings access to top talent, a more streamlined recruitment process and provides valuable industry insights, something especially vital given how fast things evolve within this space."

To learn more about life science recruitment at CSG Talent, explore live life science vacancies here, or get in touch with our expert life science and diagnostics team here.