This is a senior level role working within the Data and Translational Sciences team of a global pharma. The organisation are pushing ahead a digital transformation agenda across the entire company and this is a great opportunity to participate in and drive the innovations that will continue transform the ways in which we gain insights from an ever-growing digital landscape in the use and development of medicines.
The goal of the Patient Data Analytics team is focused on developing and using advanced analytical approaches in the context of diverse multimodal patient data - to generate insights to inform disease or patient understanding to support new drug target identification, repurposing or indication expansion; population stratification and to support design or interpretation of clinical trials.
With experience in the application of the appropriate machine learning approaches, and an appreciation of how to acquire and process the appropriate data sources, a successful candidate will support the team in generating impact for the R&D organization in the scope of disease and patient understanding in areas such as: target and drug discovery, indication expansion, disease and patient stratification, prediction of disease course, drug response, safety and in support of clinical trial design/interpretation.
*Championing the value of data driven insights with key stakeholders
*Delivering advanced analytics AI/ML projects personally or through collaborations internally or externally.
*Identification of key solutions, tools and methodologies to support the drug development portfolio.
*Identify and understand relevant data sources that can be used for patient phenotyping studies
*Deliver projects in compliance with data governance policies around patient data use
*Communication of scientific results inside and outside the team with all relevant stakeholders.
*Active collaboration with relevant stakeholders across the community (internally and externally) to support the delivery of solutions.
*Understanding the landscape of relevant AI/ML tools and the cutting edge of evidence generation
*Attend conferences and other related events
*M.Sc. or PhD (preferred, or equivalent) in Mathematics, Computational Biology, Health Data Science or Statistics with experience in the application of analytical approaches to support drug development or clinical development.
*Experienced in computational analyses of patient-derived data and transformation of analyses into insights, particularly in the context of supporting clinical decision making.
*Understanding, knowledge and practical experience with a suitable range of statistical, data science and specifically ML/AI based methods, including deep learning.
*Experience with data cleaning/munging and analysis in the context of health data.
*Experience interpreting and critically appraising real world evidence (RWE) studies.
*Experience in the successful delivery of results in coordination with other data scientists and domain experts.
*Programming skills in appropriate data processing platforms (R and Python are desirable).
*Practical experience with relevant deep learning frameworks, e.g., Tensorflow, PyTorch.
*Experienced in using bioinformatic tools and databases for analyzing DNA, RNA or other omics data.
*Experience in communicating study results in a compelling manner to stakeholders
*Experience delivering projects on time and within budget (if applicable)
There are some great benefits on offer with this role including a competitive salary, pension, and the opportunity to work with some of the best talent in the industry.
Please contact Harvey Uppal at firstname.lastname@example.org or call (+44) 121 616 3407 to discuss this opportunity further.
Keywords: Principal, Scientist, Data, Science, AI, ML, Clinical, Patient, Healthcare, Statistical, Project, Leadership, Insights, Analysis, Bioinformatics, Genomics, Biology, Pharma, RWE, Tensorflow, UK.
You must be eligible to work in the UK. Learn more
- Agency: Paramount Recruitment
- Reference: PSPDAUCB
Website: Paramount Recruitment
- Updated: 14th April 2021
- Expires: 12th May 2021