Company Description: PEP Health uses advanced AI technology to transform millions of online patient reviews from across the web and social media into actionable insights. These real-time, large-scale insights help healthcare payers and providers understand patient experience and improve services. The organization focuses on leveraging data to inform decisions that enhance care quality, patient satisfaction, and operational performance. PEP Health is virtually headquartered in London and operates across the UK and USA.
Role Description: The Data Insights Analyst role is a full-time, remote but UK based, position. This role involves analyzing patient review data and related datasets to generate meaningful insights for healthcare payers and providers. The analyst will design and run analyses, write reports, and translate complex findings into clear, understandable narratives for internal teams and external clients. The role requires use of SQL databases and Jupyter notebooks to write presentations, while also contributing to methodology improvements and ensuring data quality across projects.
What You’ll Be Doing
- Analysing in-house and external data sources to identify trends, patterns, and actionable insights
- Writing reports, presentations and visualisations for clients and internal stakeholders
- Using statistical modelling, predictive analytics and, where appropriate, machine learning techniques to generate actionable insights
- Taking ownership of complex analytical projects from initial scoping and requirements gathering to successful project delivery
- Writing long-form presentations that translate analytical findings into clear, commercially relevant recommendations
- Presenting complex information in a way that engages non-technical audiences
- Collaborating with data engineers to improve data collection, storage and quality
Qualifications
- 2+ years’ experience as a data or insights analyst in a commercial setting
- Strong analytical skills to interpret complex datasets, identify patterns, and support evidence-based conclusions
- Experience with machine learning models and statistical techniques to explore large textual datasets
- Proficiency in data analytics, including using tools such as SQL, Python and Jupyter notebooks to manipulate and visualize data
- Demonstrated experience querying large, cloud-based datasets to identify trends, patterns, and actionable insights
- Bachelor’s degree or equivalent experience in a quantitative related field (e.g., Data Science, Statistics, Maths)
- Familiarity with NLP models and patient experience data is an advantage
