Remix launched with a vision to transform patient’s lives through modulation of RNA processing. Our breakthrough science provides a path to identify small molecules that impact the expression of disease driving mRNAs and proteins. We take on the challenge of addressing drug targets in diseases of high unmet medical need to bring new therapeutic options to patients. Remix has a commitment to demonstrate the highest levels of scientific integrity with urgency because those patients are counting on us to deliver. With an in-house technology platform built from scratch, we have rapidly generated multiple drug discovery programs that are advancing towards the clinic.

We seek a highly motivated, experienced translational bioinformatic leader to join our team located in Watertown, MA. As a translational bioinformatician reporting to the Head of bioinformatics and data science, this person will direct in collaboration with a cross-functional team of scientists and clinical experts the translational strategy and multi-omics analysis of complex data sets for the different projects leading to the development of novel RNA processing medicines. The ideal candidate will have a strong background in bioinformatics as well as translational expertise in one or more target areas relevant to Remix, especially oncology and/or neurodegeneration, and will be driven to succeed within a hypothesis-driven, team-oriented, and interdisciplinary biotech environment. The individual will be expected to contribute to all stages of drug development, supporting the translational efforts from the preclinical stage to marketing. 

Principle duties and responsibilities:

• Engage with the clinical and biomarker teams to organize and extract evidence of activity and other biological insights from emerging clinical data
• Analyze complex multi-omics data sets across various modalities and connect insights and observations to clinical endpoints, highlighting possible indication expansion for key targets
• Contribute to the translational computational strategy for a number of exciting early-and late-stage targets in the Remix portfolio, as well as partnered targets across diverse disease areas
• Mine public and private multi-omic datasets including real-world data relating to Remix target areas for insights into patient stratification and biomarker strategies for early and late stage programs across Remix target areas, with a current focus on oncology and neurodegeneration
• Work with internal groups at Remix as well as external partners to solve problems using cutting-edge data analysis and visualization
• Participate and thrive in a culture of effective collaboration between experimental and computational scientists

Qualifications:

• PhD in Computational Biology, Bioinformatics, or Computer Science, with 7+ years of total experience working in disease target areas relevant to Remix, especially oncology and/or neurodegeneration
• Outstanding bioinformatics programming skills in at least one language relevant to data analysis such as Python or R
• Ability to effectively communicate methodologies and results with colleagues, including bench scientists, research management, and project team leaders
• Knowledge of RNA biology a plus, especially RNA splicing
• Strong leadership skills
• Strong problem-solving and troubleshooting skills
• Ability to work in a dynamic and fast-paced environment independently and efficiently
• Authorized to legally work in the US

Remix values diversity and is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person’s race, color, gender, age, religion, national origin, ancestry, disability, marital or veteran status, genetic information, sexual orientation, or any other legally protected status. Remix will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Note to Third Party Staffing Agencies: Please do not forward any agency resumes. Remix Therapeutics is not responsible for any fees related to resumes that are unsolicited.