Job description

Requirements

  • Entry level
  • No Education
  • Salary to negotiate
  • London

Description

Job Description


We are looking for a Data Scientist who is keen to apply data engineering and machine learning tools and products at the cutting-edge of life sciences. The primary focus of the role is:


Use and understand client requirements to apply ML-focused solutions to highly complex, rich patient-level medical data

Communicate technical concepts and analytical outputs to a diverse set of stakeholders (internal and external)

Own the delivery of client-facing projects from a technical perspective: Working closely with data engineers, data scientists and consultants in an agile environment to deliver work that adheres to the processes and quality standards set by the team

Proactively provide feedback on existing processes and identify areas for improvement across the workflow


Qualifications


Appetite for applying new and existing technologies to challenging problems in health care, i.e. motivated by solving the problem

Postgraduate degree or higher in a technical or scientific domain

Experience of analytical / machine learning projects in academia or commercial sector

Experience in scientific programming languages such as Python and R

Knowledge of supervised machine learning methods, such as regularised regression, ensemble tree-based models (e.g. xgboost), support vector machines, deep learning methods, etc.

Good grasp of classical statistical methods, such as fitting regression models, inference testing and sampling.

Excellent organisation skills with an appetite for working a fast-paced environment

Excellent written and spoken communication skills, including ability to present technical concepts to lay audiences, write analysis plans for projects, contribute to proposals / grant applications, pitch ideas effectively and persuasively to clients / internal stakeholders, etc.

A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently, able to work as part of a cross-functional team.


Additional Information


Knowledge of healthcare patient-level data.

Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilisation, etc.

Work in bioinformatics.

Knowledge of healthcare / life science issues involving Real-World Evidence.

Experience with patient-level, longitudinal data.

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