Principal Developer, Technology and Scientific Computing

Job Description Summary

The Principal Developer will work as part of an interdisciplinary team to develop solutions and tools that enable associates working on analyses and reporting activities in clinical trials. They will work across Advance Quantitative Sciences (AQS)to gain an appreciation of the user experience today and work with Product Owners to deliver progress in high impact areas. This role will focus on enabling the use of open-source tools across the spectrum of activities in AQS.

 

Job Description

Major accountabilities:

• Responsible and accountable for the development of technical tools (packages, applications, etc.) that enable clinical trial teams.
• Active participation in the full development cycle of tools from gathering user requirements, prototyping, demos and to training and support.
• Engagement in the user experience of our associates to identify and drive opportunities for continuous improvement and modernization
• Contribute to the evolution and uptake of good data science practices
• Documentation of tools and processes to support modernization in an inclusive manner
• Appetite to engage in external communities and showcase our work in external settings

Key performance indicators:

• Timely execution of of projects and data requests -Feedback from project sponsors and key stakeholders

Minimum Requirements:
Work Experience:

• MSc with 5+yrs relevant experience in a quantitative / computational science (e.g. bioinformatics, machine learning, statistics, physics, mathematics, engineering...) with some relevant work experience as a data scientist / biostatistician
• Strong experience with open-source language/s (R or Python) for data wrangling, analyses and exploration
• Experience in good data science practices (virtual environments, versioning, code review etc.)
• Solution-oriented mindset with a collaborative spirit
• Good written English

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Skills Desired

Algorithms, Computer Programming, Computer Science, Computer Vision, Data Science, People Management, R&D (Research And Development), Waterfall Model