Data Scientist

3 weeks ago

Macclesfield Cheshire, United Kingdom SRG Full time

Respectfully, please DO NOT apply if your experience has not been gained working on biological data.

We are looking for an exceptional Data Scientist to drive the development of innovative AI and ML solutions for biomarker discovery, drug response prediction, and clinical decision-making support. This role offers a unique opportunity to leverage AI/ML technologies to enhance cancer patient outcomes.

This position requires a strong foundation in traditional statistical methods and expert knowledge of ML methodologies to analyse complex LC-MS/MS-derived datasets.

Collaborating closely with wet lab and bioinformatics teams, you will play a pivotal role in establishing a new precision medicine approach, aiming to create a single test predictive of a patient’s response to various therapies.

Are you experienced in Machine Learning (ML) and Deep-Learning (DL) methods, with over 5 years of expertise? This role involves applying various ML approaches to complex molecular and clinical data for biomarker discovery. Additionally, proficiency in a cloud platform like GCP, AWS, or Azure is key, along with experience in source control and software lifecycle management.

If you have a strong track record in structured problem-solving within interdisciplinary settings and a solid understanding of biochemical and molecular biological systems, this could be the perfect fit for you. A passion for mentoring and supporting colleagues, especially in ML best-practices, is highly valued.

We are looking ideally for individuals with expertise in Bayesian statistical methods, bioinformatics pipelines for proteomics data analysis, and experience in regulated environments. If you have a PhD or equivalent experience in these fields and are fluent in R, Python, or C++ and passionate about applying data science to revolutionise precision medicine and drive significant advancements in cancer treatment, this is an exciting opportunity to make a meaningful impact in the field.

Onsite/hybrid/remote options available.

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