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Scientific Data Analyst Investigator

2 months ago

Stevenage, Hertfordshire, United Kingdom GlaxoSmithKline Full time
About the Role

We are seeking a highly skilled Data Scientist Investigator to join our team at GlaxoSmithKline. As a Data Scientist Investigator, you will play a key role in driving business growth and innovation by leveraging data analytics and scientific expertise.

Key Responsibilities
  • Deliver Data Solutions: Design and develop data solutions with measurable cross-organizational impact and value, including code libraries, analytical pipelines, data processing pipelines, visualizations, and front-end tools.
  • Partner with Stakeholders: Collaborate with research scientists and stakeholders to understand data needs and deliver appropriate solutions, working with your Team Leader to prioritize your book of work.
  • Contribute to Business Goals: Contribute to the overall Data & Predictive Sciences goals and objectives via implementation of relevant components of those objectives.
  • Develop and Foster a High-Performing Team Culture: Develop and foster a high-performing team culture of collaboration, curiosity, consistency, agility, quality, peer review, and continuous improvement.
Requirements
  • PhD in Bioinformatics or Relevant Scientific Domain: PhD in bioinformatics or a relevant scientific domain, or extensive years of professional experience with a Master's degree.
  • Programming Skills: Proficiency in one or more programming languages, such as Python, R, Java, including toolchains for documentation, testing, and operations.
  • Image Analysis Experience: Experience in using image analysis tools like ImageJ, CellProfiler, 10X Space Ranger, and Loupe Browser.
  • Scientific Knowledge and Acumen: Scientific knowledge and/or acumen to understand GSK's biological research data.
  • Experience Translating Complex Data: Experience translating complex multi-dimensional data into biological understanding.
Preferred Qualifications
  • Strong Experience with Image Processing: Strong experience with image processing and analysis techniques, particularly for analyzing histological images or spatial data.
  • Strong Knowledge of Statistical Methods: Strong knowledge and experience with statistical methods and machine learning techniques applied to high-dimensional data.
  • Experience with Bioinformatics Tools: Experience with bioinformatics tools and packages, such as Seurat, Scanpy, SpatialIDE, and Giotto, for analyzing transcriptomics data.