Data Scientist - Associate, New Grad

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Job Summary:

Epicrispr Biotechnologies is an early-stage biotechnology company focused on innovative epigenome engineering tools for therapeutic applications. The Associate Data Scientist will collaborate with experimental biologists to analyze high-throughput biological data and contribute to the development of bioinformatics tools.

Responsibilities:

• Lead collaborative efforts with experimental biologists and bioengineers on experimental design and data analysis approaches to drive strategic therapeutic and engineering goals.

• Analyze complex high-throughput datasets.

• Independently design, implement, and optimize bespoke analysis pipelines tailored for in-house screening efforts.

• Communicate analysis results effectively across teams, bridging the gap between experimental scientists, data scientists, and non-technical stakeholders.

• Contribute to and support the continuous improvement of bioinformatics tools, workflows, and methods.

Qualifications:

Required:

• Masters required or Ph.D. preferred in Bioinformatics, Computational Biology, Biophysics, Genetics/Genomics, Bioengineering, Computer Science, Statistics, or a related quantitative field, with 0-2 years of experience in a relevant industry or academic environment; or MS in one of the above fields with 2-4 years of industry/academic experience, or BS in a relevant field with 5+ years of industry/academic experience.

• Proficiency in programming languages such as Python or R (preferably both), with a focus on exploratory data analysis and pipeline development.

• Demonstrated ability to effectively communicate complex scientific concepts and results to both technical and non-technical stakeholders.

• Strong experience with experimental design, working cross-functionally with wet-lab scientists, and contributing to multidisciplinary research efforts.

Preferred:

• Expertise in gene regulation, epigenetics, CRISPR biology, and/or gene therapy.

• Extensive experience analyzing high-throughput sequencing data, including CRISPR screens, RNA-seq, ATAC-seq, ChIP-seq, WGBS, scRNA-seq, and similar datasets.

• Experience working with cloud computing platforms such as AWS for large-scale data analysis.

• Familiarity with GitHub for version control and collaborative code development.

• Theoretical and practical knowledge of machine learning and deep learning methodologies for biological data analysis.

• Familiarity with lentiviral vector design, packaging, transduction, and the creation of stable cell lines.

Company:

Epic Bio's strength is a relentless focus on ushering in a new era of gene regulation. Founded in 2018, the company is headquartered in South San Francisco, California, USA, with a team of 11-50 employees. The company is currently Growth Stage. Epicrispr Biotechnologies has a track record of offering H1B sponsorships.