Principal Bioinformatics Software Engineer, Clinical Pipeline
Job Description 6000! That's the number of associates in the Novartis Institutes for BioMedical Research (NIBR). This division is the innovation engine of Novartis, focusing on powerful new technologies that have the potential to help produce therapeutic breakthroughs for patients.
NIBR Oncology is seeking an experienced software engineer with domain knowledge in bioinformatics to help develop applications to marshal, transform and visualize complex data sets from the clinical research space, such as genotypic and other omics biomarker assay outputs. While exciting, this sometimes presents a challenge-and we want you to help! Specifically, in this hands-on role, you will collaboratively architect and design software solutions that accelerate the work of our data scientists and lead or contribute to efforts to enhance and improve existing systems. You will work within a larger Engineering team following Agile practices and collaborate closely with data scientists to deliver the most impactful solutions possible. You should have a strong software engineering background and an understanding of the scientific domain.
Your responsibilities include, but are not limited to: - Design and build performant, well tested NGS production data processing pipelines (scRNA, bulk RNA, targeted DnaSeq, etc.)
- Contribute to joint development efforts with data scientists on tooling to filter and QC genomic variant calls
- Work on early-stage data analysis for new assays or novel data types
- Lead and manage development efforts, define project roadmaps, handle production support requests
- May manage, coach and mentor a junior developer
This position will be located at the Cambridge, MA site and will not have the ability to be located remotely. This position will not require travel as defined by the business (domestic and/ or international)."
EEO Statement The Novartis Group of Companies are Equal Opportunity Employers and take pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.
Minimum requirements What you'll bring to the role: - A minimum 5 years of experience working in bioinformatics software engineering
- A BS Degree
- Experience working with clinical omics data in a regulated production environment strongly preferred (CLIA, CAP)
- Experience in Python development required
- Experience with R, Java and SQL are preferred
- Proficiency in a Linux environment is required
- Previous experience with HPC clusters is preferred
- Practical knowledge of software engineering, Agile development methodologies and development operations best practices is required
- Experience working collaboratively with a cross-functional team of engineers and data scientists is required
Why Novartis?
766 million lives were touched by Novartis medicines in 2021, and while we're proud of this, we know there is so much more we could do to help improve and extend people's lives.
We believe new insights, perspectives and ground-breaking solutions can be found at the intersection of medical science and digital innovation. That a diverse, equitable and inclusive environment inspires new ways of working.
We believe our potential can thrive and grow in an unbossed culture underpinned by integrity, curiosity and flexibility. And we can reinvent what's possible, when we collaborate with courage to aggressively and ambitiously tackle the world's toughest medical challenges. Because the greatest risk in life, is the risk of never trying!
Imagine what you could do here at Novartis!
Commitment to Diversity & Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.
Accessibility and Reasonable Accommodations: Individuals in need of a reasonable accommodation due to a medical condition or disability for any part of the application process, or to perform the essential functions of a position, please send an e-mail to tas.nacomms@novartis.com or call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
Vaccine Policy: While Novartis does not require vaccination at this time, for certain Novartis sites in the US all associates and candidates may be required to either upload an image of their COVID-19 vaccine card demonstrating proof of full vaccination for COVID-19 (or other similar evidence of vaccination) or proof of a negative COVID-19 test taken by the associate or candidate within the past seven days to enter any of our sites and/or customer office or healthcare facility, as well as prior to participating in other work related off-site meetings. Employees working in customer-facing roles must adhere to and comply with customers' (such as hospitals, physician offices, etc.) credentialing guidelines, which may require vaccination. As required by applicable law, Novartis will consider requests for reasonable accommodation for those unable to be vaccinated. This requirement is subject to applicable state and local laws and may not be applicable to employees working in certain jurisdictions. Please send accommodation requests to Eh.occupationalhealth@novartis.com.
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network.
Business Unit Oncology NIBR
Work Location Cambridge, MA
Company/Legal Entity NIBRI
Functional Area Data Science
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