Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a team to assess real-world data for consumer health products.
- Company: Work with a global leader in consumer healthcare, making a real impact.
- Benefits: Enjoy remote work flexibility and competitive pay of £50-70 per hour.
- Why this job: Contribute to meaningful research while collaborating with diverse teams.
- Qualifications: MSc or PhD in relevant fields and experience with health datasets required.
- Other info: This is a 6-month contract role with opportunities for growth.
Job Description
Epidemiologist / Data Scientist\\n\\nLocation – Remote \\n\\nDuration – 6 months \\n\\nRate – circa. £50-70 per hour (based on experience)\\n\\nAt SRG we are partnered with a global consumer healthcare company who are searching for an experienced Epidemiologst or Data Scientist to join their experienced team. This is an important role, supporting the business for 6 months, where the ideal candidate will bring a proven track record of assessing the feasibility of utilising existing real-world data (RWD) sources, to support the generation of real-world evidence (RWE) for consumer health products.
This will aid the identification of potential applications for RWE studies that use these data sources to aid research and decision-making.\\n\\nThe Role includes the following responsibilities:\\n\\nExplore feasibility of RWD sources to support RWE generation across categories and Bus\\nAssess data completeness, timeliness, representativeness, coding systems and capture of relevant endpoints and exposures\\nGenerate insights from data to inform clinical and business strategies\\nDeveloping feasibility reports and recommendations\\nEffectively communicate findings and insights to internal stakeholders Collaborate closely with cross-functional teams, including Safety, Regulatory Affairs, Categories and Business Units to ensure data requirements are aligned with strategic needs \\n\\nYour skills and experience:\\n\\nMSc or PhD in Epidemiology, Biostatistics, Health Data Science, or related disciplines\\nDemonstrable experience working with public health or healthcare datasets\\nExperience or good understanding of the use of social media data for RWE generation\\nStrong understanding of health data structures, retrospective RWE methods, and population health research\\nProficient in data analysis tools such as R, Python, and SAS.\\nSkilled in data quality assessment\\nAbility to synthesise complex data characteristics and communicate them clearly\\nAnalytical mindset with exceptional attention to detail\\nStrong written and verbal communication skills\\nComfortable working independently \\n\\nTo Apply:\\n\\nIf you want to find out more about this role or would like to make an application, click below or contact Theo Charles\\n\\nCarbon60, Lorien & SRG – The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy
Epidemiologist / Data Scientist employer: SRG
Contact Detail:
SRG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Epidemiologist / Data Scientist
✨Tip Number 1
Familiarise yourself with real-world data (RWD) sources relevant to consumer health. Understanding how these datasets can be utilised for generating real-world evidence (RWE) will give you a significant edge during discussions with potential employers.
✨Tip Number 2
Brush up on your data analysis skills, particularly in R, Python, and SAS. Being able to demonstrate your proficiency in these tools during interviews will show that you're ready to hit the ground running.
✨Tip Number 3
Prepare to discuss your experience with public health or healthcare datasets. Be ready to share specific examples of how you've assessed data quality and generated insights, as this will highlight your practical knowledge in the field.
✨Tip Number 4
Network with professionals in the epidemiology and data science fields. Engaging with others in the industry can provide valuable insights and potentially lead to referrals, making it easier for you to land the job.
We think you need these skills to ace Epidemiologist / Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in epidemiology, data science, and any specific projects involving real-world data (RWD). Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the field and outlines how your skills align with the responsibilities mentioned in the job description. Mention specific experiences where you've successfully assessed RWD sources or generated insights.
Highlight Technical Skills: Clearly list your proficiency in data analysis tools such as R, Python, and SAS. Provide examples of how you've used these tools in previous roles to analyse health data or generate real-world evidence.
Showcase Communication Skills: Since the role requires effective communication of findings, include examples in your application that demonstrate your ability to convey complex data insights clearly to stakeholders. This could be through presentations, reports, or collaborative projects.
How to prepare for a job interview at SRG
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in data analysis tools like R, Python, and SAS during the interview. Be prepared to discuss specific projects where you've successfully used these tools to analyse health data or generate real-world evidence.
✨Demonstrate Your Understanding of RWD
Familiarise yourself with real-world data sources and be ready to discuss their feasibility for generating insights. You might be asked about your experience with public health datasets, so have examples ready that showcase your analytical mindset and attention to detail.
✨Communicate Clearly
Since the role involves collaborating with cross-functional teams, practice explaining complex data concepts in simple terms. This will demonstrate your ability to effectively communicate findings and insights to stakeholders who may not have a technical background.
✨Prepare for Scenario-Based Questions
Expect questions that assess how you would handle specific situations related to data quality assessment or generating insights from data. Think of scenarios from your past experiences where you had to make decisions based on data analysis and be ready to share those stories.
