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Data Scientist position- Causality Inference and Discovery
martes, 18 de febrero de 2020

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 Discovery Sciences Team
Sensyne Health are seeking to add Causality expertise to the Data Science team within our Discovery Sciences function, helping the business deliver on our mission to accelerate medical research and improve patient care.

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.

Your Statistical expertise and proficiency in mathematical analysis especially in the area of adapting causal discovery and inference methods will help unlock further insights from real world medical data, and enable the team to deliver on our promise of discovering robust clinical insight that will ultimately make a difference to the lives of patients across a range of therapeutic areas.

We love to work with people who are collaborative and who will proactively seek to share knowledge. Individuals who have the confidence to speak up when needed and the pragmatism to accept compromise. We'll give you the autonomy to do the best thing, not just the easiest thing. We all have a strong sense of team and are able to support those around us whilst keeping moving forward.

How you'll help
Building and implementing Data Science and Statistics solutions to provide actionable intelligence to support business decision-making within life sciences
Support and guide other researchers on best practices in statistical/mathematical analysis through all stages of project development
Contribute to the development of mathematical/statistical/computational models to identify and test causal relationships in data
Publish research results in national and international conferences and scientific journals

Requirements
Higher university degree (MSc or PhD) in Computer Science, Engineering, Mathematics, Physics, Statistics, Biostatistics, Econometrics, or a relevant field of applied mathematics with focus on data science or statistics
Broad statistical awareness with the ability to develop innovative experimentation and analysis methods, formulate hypotheses based on real-word data, uncover causal mechanisms, and build informative visualizations.
(must have) Experience with causal discovery (e.g., by building directed graphical causal models) or causal inference (e.g., Mendelian randomization, instrumental variable analysis, structural equation modelling)
Solid programming experience in one or more scientific programming language: R, Python, C/C++, etc.
(desirable) hands-on experience with (causal) Bayesian networks
(desirable) hands-on experience with SQL/tidyverse/ggplot
(desirable) experience of analysing clinical/healthcare data is a bonus
Benefits
Company share option scheme
5% employer matched Pension scheme
BUPA Health Insurance including Partners and Children cover
Free Gym Membership
Cycle to work scheme
A challenging and fun environment that rewards results
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