Data Scientist

The Company

Abtrace is a health tech company based in London, with a team of doctors, researchers, developers and data scientists that bring together software engineering, machine learning expertise and medical experience to build clinical algorithms to support primary care clinicians.

The team is dedicated to creating digital health software to deliver Population Health interventions individualized to patients. This involves the continuous scanning of the entire health record of a patient to detect signals of deterioration, early onset of new disease and opportunities for preventative interventions.

 We work with over 250 primary care practices covering 2.5 million patients.

The Role

We are looking for a Data Scientist (Mid/Senior) to join our team who works well in a fast moving team and communicates effectively with non-technical team members.

The core duty of the position will be the analysis of longitudinal healthcare datasets and development of predictive models from those datasets. The ideal candidate will have an excellent knowledge of Python and be proficient in tools from the data science ecosystem (scikit-learn, pandas, Tensorflow, Pytorch, spaCy, SQL and similar).

Responsibilities

• Analysis of clinical datasets
• Designing predictive algorithms and performing machine learning experiments on clinical datasets
• Work with a small, close knit, diverse multi-disciplinary team of developers, data scientists and doctors

Requirements

• Proficiency in Python and SQL
• Excellent knowledge of machine learning and MLOps
• Experience in Natural Language Processing
• Experience with AWS cloud infrastructure

Benefits

• Salary range £70,000 – £80,000, depending on experience
• Private Pension
• Generous maternity/paternity leave
• Flexi working & possibility for remote working
• Company’s office in Paddington – easy commute and comfortable surroundings
• Motivated, highly functioning, multi-disciplinary team
• Opportunity to be involved in ground-breaking technology impacting patient health