Data Scientist, Molecular Modalities & Preclinical Discovery in Stevenage

The new Data and Predictive Sciences (D&PS) function in Research Tech is focused on harnessing the power of GSK’s data-as-an-asset to drive research productivity and unlock upper quartile ambitions. As an Investigator in the Data Sciences team aligned to Molecular Modalities Discovery and Pre-Clinical Sciences, you will collaborate with scientists in Research Tech functions to develop and deliver consistent high-quality, high-impact industry-leading data sciences solutions ready for industrialization.

Data & Predictive Sciences will only be successful by working in close collaboration with Research Tech, TAs, GSK Tech, AIML, Risk & Compliance, and across lines within the function itself, and by developing and fostering a high-performing team culture of collaboration, curiosity, consistency, agility, quality, peer review, and continuous improvement with a relentless focus on enabling value realization through end-user uptake and measuring impact. If this sounds like a culture you will thrive in, please apply.

Key Responsibilities include, but are not limited to:

• You will be expected to consistently deliver solutions with measurable cross-organizational impact and value, leveraging existing or planned infrastructure from partner functions in SD&T and Onyx where possible.
• You will be responsible for facile data collation, preparation and storage and exploratory data analysis to identify trends, patterns and anomalies in the data and communication of findings to collaborators.
• You will develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality.
• You will carry out basic project management for your projects and manage communications accordingly.
• You will contribute to the overall Data & Predictive Sciences goals and objectives via implementation of relevant components of those objectives.
• You will collaborate with research scientists and stakeholders to understand data needs and deliver appropriate solutions.
• You will work with your Team Leader to prioritize your book of work.
• You will have a strong commitment to teamwork and partnership with all stakeholder functions.
• You will work with other data scientists to build an understanding of the business context, systems, environment, strategy and people aligned to this area.
• You will be a standard bearer for proper ways of working, engineering discipline, process improvement, etc. for the entire Research Tech organization.
• You will work across Data Sciences teams to contribute to peer review, quality, consistency and enterprise thinking.
• You will seek and be responsive to peer feedback to grow your skills and impact.
• You will continuously improve your skills and knowledge to keep abreast of advancements in this rapidly evolving field.

Basic Qualifications:

• PhD in a data sciences, bioinformatics or Life Sciences discipline.
• Experience in biopharmaceutical or pharmaceutical discovery and development with an emphasis on chemistry, biology, DMPK or related scientific disciplines.
• Experience in one or more programming languages (SQL DDL/DML, Python or R preferred).
• Experience in assembling (preparing raw data for analysis), analysing, and visualizing complex scientific data.
• Experience with databases, data warehousing, building data pipelines, big data technologies and working with large scale biology, chemical or structural data.
• Experience working as part of a team in a matrix environment and delivering impactful solutions.

Preferred Qualifications:

• Knowledge of statistical analysis, machine learning, and data manipulation libraries (e.g., pandas, scikit-learn, TensorFlow).
• Familiarity and/or experience with concepts related to Data Fabric, Data Products, and Data as an asset.
• Knowledge/experience in bioinformatics, cheminformatics, transcriptomics, statistics, image analysis, protein and small molecule structure.