(Senior) Scientist, Data Product
Cambridge, MA
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Deep Genomics
Revolutions in AI, biology and automation are enabling a new approach to medicine. Deep Genomics is at the forefront.Where You Fit InWe are seeking a highly motivated and collaborative (Senior) Computational Biologist to join our AI-guided RNA editing drug development team. You will play a key role in the discovery, characterization, and optimization of RNA editing targets and therapies. This position offers the opportunity to work at the intersection of computational biology, RNA therapeutics, and machine learning in a multidisciplinary and fast-paced environment. The successful candidate will work closely with cross-functional partners— Biology, Machine Learning, and Engineering teams—to integrate computational approaches into all stages of research. This is a full-time position in Cambridge reporting to a Principal Scientist on the Data Product team.
Key Responsibilities
- Design and implement computational pipelines for discovery-stage and preclinical programs. Build and maintain robust, scalable analysis pipelines and workflows to capture and analyze large-scale experimental datasets. In collaboration with the ML team, produce data packages that demonstrate the value of the AI platform in drug discovery.
- Collaborate with users and the engineering team to optimize the computational discovery infrastructure enabling high-quality accelerated results.
- Contribute to the design of experiments for model evaluation in partnership with the Target Identification and experimental teams.
- Identify and integrate external datasets in collaboration with the engineering and machine learning teams.
- Communicate findings and incorporate feedback with internal and external audiences through presentations and publications.
Basic Qualifications
- PhD in Computational Biology, Bioinformatics, Genomics, or a related field; or M.Sc. with 2+ years of relevant experience.
- Demonstrated expertise in large-scale NGS data analysis, including amplicon sequencing, RNA-seq, and other molecular profiling methods.
- Strong background in RNA biology, particularly RNA editing, splicing, or transcriptome analysis.
- Strong programming skills (e.g., R, Python), with experience in cloud computing, data management, and bioinformatic tools.
- Proven ability to manage computational aspects of cross-functional projects/programs and communicate complex computational concepts to both technical and non-technical audiences.
- Strong analytical and problem-solving skills, with a focus on delivering practical, impactful solutions.
Preferred Qualifications
- Familiarity with AI/ML applications in drug discovery.
- Experience in a clinical-stage biotechnology company or RNA-based drug development.
- Understanding of RNA editing mechanisms, ADAR systems, or programmable editing systems.
- Track record of scientific achievement through publications, patents, or presentations in computational biology or bioinformatics.
What We Offer
- A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery.
- Highly competitive compensation, including meaningful stock ownership.
- Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program.
- Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
- Maternity and parental leave top-up coverage, as well as new parent paid time off.
- Focus on learning and growth for all employees - learning and development budget & lunch and learns.
- Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, MA - a global center of biotechnology and life sciences.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Bioinformatics Biology Data analysis Data management Drug discovery Engineering Machine Learning PhD Pipelines Python R Research
Perks/benefits: Career development Competitive pay Equity / stock options Flex hours Flex vacation Health care Parental leave Startup environment Unlimited paid time off
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