About Us:

At Sensyne Health we combine technology and ethically sourced patient data to help people everywhere get better care. To do this, we have created a unique partnership with the NHS that delivers a return to our partner Trusts and unlocks the value of clinical data for research while safeguarding patient privacy. Alongside this, we develop clinically validated software applications that create clinician and patient benefit while providing highly curated data. Our products include vital-signs monitoring in hospitals and patient-to-clinician apps to support self-care and remote monitoring of gestational diabetes and chronic diseases such as COPD and heart failure.

The Team:

We are an agile team of Clinically led data science specialists who use our proprietary clinical AI technology to analyse ethically sourced, clinically curated, anonymised patient data to solve serious unmet medical needs across a wide range of therapeutic areas, enabling a new approach to clinical trial design, drug discovery, development and post-marketing surveillance. The nature of our team is collaborative with an emphasis on genuine passion for healthcare.

The Role:

As a leading member of a dynamic, multi-disciplinary team of scientists passionate about reinventing the way new medicines are developed, you will bring your deep understanding of data science and medical statistics to enhance our ability to perform key research, data visualisation, insight gathering and decision making from big data and real world evidence.

This role will be reporting into our Head of Research who you will work closely with in order to lead the design and selection of analytical tools, state-of-the-art data integration techniques that ensure we uphold our strict ethical policies, while releasing the clinical insights in the real-world data.

Your work with experts in artificial intelligence, deep learning, informatics, statistics, drug discovery and clinical translation/commercialisation will enable us to discover robust clinical insight that will ultimately make a difference to the lives of patients across a range of therapeutic areas.

How you'll help:

• Lead in the design, execution and reporting of RWD research projects
• Lead and inspire a small team of data scientists, while collaborating with the wider team
• Be a technical lead on Causal Inference and its application to novel healthcare/clinical research projects
• Clinical project support to guide decision making and create analytical solutions to address questions of interest to our pharma stakeholders.
• Provide scientific and methodological reviews
• Perform robust data analysis and communicate results with sophisticated visualisation methods
• Create and implement statistical & machine learning algorithms, assessing their effectiveness through solid validation workflows
• Assisting with the publication of scientific papers and abstracts

Requirements:

• Be confident to be a technical lead on Causal Inference and/or Causal Discovery and to lead and support the team on statistical analysis (e.g. survival analysis, matching)
• Enjoying leading a small team
• Expertise with the analysis of real-world and clinical data and the support of projects within Life Sciences
• Strong knowledge of current data science, machine learning, and visualisation tools
• Proficiency with programming and scripting language R to communicate with your direct team
• Demonstrate the ability to prioritise tasks and meet multiple deadlines on concurrent projects
• PhD (or equivalent advanced degree/experience) in an applied quantitative field such as Computer Science, Applied Statistics, Biostatistics, Mathematics etc.
• Excellent verbal and written communication and presentation skills; excellent organisational skills; and excellent interpersonal skills to work effectively in a diverse team
• Ability to lead projects; assess client requirements, create project plans, project management and execute in a collaborative environment in a fast-paced company
  

• Proficiency with programming and scripting language Python to work with our Machine Learning teams
• Experience in any of these is a plus: SQL, NoSQL, Shiny, Graph database, Knowledge Graph, Tidyverse
• Experience working with the Azure

• Company share option scheme
• 5% employer matched salary sacrifice Pension scheme
• Life Assurance & Income protection
• A range of health, wealth and lifestyle benefit plans including BUPA, Gym and holiday trade options
• Electric Vehicles & Cycle to work schemes
• Proactive career development planning