Mantra Bio is seeking an experienced Bioinformatician to join our Data Science, Engineering, and Technology Team. You will be a key contributor to our exosome therapeutic programs that span both early R&D and preclinical IND efforts, collaborating across Mantra Bio with Process Scientists, Preclinical Scientists, Protein Scientists, and Data Scientists. The position requires broad technical experience developing robust data pipelines and deep knowledge of applied statistics in biology, medicine, or a closely related field. You will facilitate scientists’ use of internal and public data, provide guidance on experiment design, perform statistical analysis for in vitro and in vivo experiments, and train scientists on statistical tools and methods. Together with our team of Bioinformaticians, Data Scientists and Engineers, you will expand Mantra Bio’s data-centric approach to drive good, scalable science and accelerate progress toward our therapeutic mission.
Responsibilities
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Collaborate with scientists on well-powered in vitro, in silico and in vivo experiment designs
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Identify and perform proper statistical tests for analyses ranging from small animal studies to large screening experiments
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Ingest publicly available datasets into our internal company architecture to power algorithm development by our Data Science team
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Manage time and projects efficiently to support the analysis needs of multiple groups simultaneously
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Create or verify trustworthy publication-level figures from critical in-house studies that will be presented at high-impact board and investor meetings
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Act as a general mentor to Mantra Bio employees in areas of experimental design, quality control, statistical analysis, and graphical presentation of data
Your profile:
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Master's degree in biostatistics, statistics or related field and 2+ years industry experience writing production level code required
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Expertise in Python, including scipy and matplotlib required; experience with TensorFlow, Scikit-learn, and Pytorch preferred
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Professional experience with SQL databases required; schema design and migration preferred
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Strong understanding of statistical tests and exploratory statistics, including both metrics and visualization
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Experience programmatically accessing public datasets such as UniProt, TCGA, Gene Ontology, or Gene Expression Omnibus
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Demonstrated ability to collaborate with multiple stakeholder groups, including research scientists
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Experience with Jupyter notebooks, dashboards, R, GCP, Kubernetes, TypeScript and React are nice to have
Annual Salary for this role - $120,000 to $145,000