Investigator, Data Sciences - Molecular Modalities & Pre-Clinical Sciences

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 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 valuerealizationthrough 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. To that end, 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. This also includes an understanding of the relevant internal and external high-volume data sources, validity and domains of such data in order to align with the intended business objective.
• 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.

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

• 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:

If you have the following characteristics, it would be a plus:

• Knowledge of statistical analysis, machine learning, and data manipulation libraries (e.g., pandas, scikit-learn, Tensor Flow).
• 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,…