Data Scientist

Dyad's mission is to improve the delivery and efficiency of healthcare. We are building a platform to model and manage the flow of information within healthcare organisations, improving outcomes for patients, payers, and healthcare providers. We believe data handling in current healthcare systems is needlessly complex and disconnected, leading to isolated and inefficient decision making. To showcase how this technology can advance the delivery of healthcare and improve lives, we build and deploy products for healthcare providers and payers into the UK and US markets. Dyad is an energetic, health-tech startup, currently around forty employees. Our team is growing as we explore new markets and opportunities. We are passionate about technology and its applications in worthwhile ventures. New joiners will have a significant impact on the direction of the company, as well as our culture.

Our products are founded upon our Semantic AI platform, which enables payers and providers to access cutting‑edge AI capabilities for their own use cases and applications. Our partners either use the platform APIs directly or work with us to develop applications for their use cases.

BetterLetter, our AI tool helping practices decrease their admin burden in processing clinical letters, helps providers save time, save cost, improve performance under audit and build staffing resilience.

The role involves:

• Data extraction and analysis: Work with BetterLetter, AI Platform, QARA, and Commercial to pull data from production systems, customer environments, and internal tooling. Clean, join, aggregate, and interrogate datasets with rigour in order to communicate findings to all stakeholders.
• Dashboarding and reporting: Build and maintain dashboards for internal teams and produce recurring reports that are accurate, legible, and consistent over time.
• Benchmarks and evaluations: Turn benchmark and evaluation outputs produced by the AI Platform team into documentation, reports, and visualisations that other teams can use.

Requirements include:

• A track record of applied data analysis work in a commercial setting with at least 3 years of experience.
• Experience pulling, cleaning, and analysing data from production systems along with reporting and data visualisation.
• Comfortable presenting findings to non‑technical stakeholders.
• Experience working in or alongside teams building data‑intensive products, ideally including ML or AI systems, is highly desirable.

Technical skills required:

• Python for data work: pandas, NumPy, Jupyter, plotting libraries.
• SQL across common dialects.
• A modern BI or dashboarding stack.
• Basic statistical thinking.
• Reading and interpreting evaluation outputs from AI systems.

Personal attributes include:

• Communication‑led: treats clear presentation as part of the analysis.
• Pragmatic and outcome‑focused.
• Cross‑functional by instinct.

Our hiring process includes an introductory screening interview, interviews with senior leadership and cross‑functional partners, and a final interview and offer.

Benefits include a competitive salary, company pension, 25 days of paid annual leave, flexible hybrid working environment, Employee Assistance Programme, and a modern, dog‑friendly office near Chancery Lane with free drinks.