Inzen Therapeutics is a privately held, early-stage biotechnology company exploring Thanokine Biology as a surprising and vital driver of disease. While the ability of living cells to respond to messages from other living cells is a well-established concept, Inzen has identified that living cells also respond to messages released by cells as they undergo turnover and die. We call these messages Thanokines, and the way a cell undergoes turnover dramatically alters the Thanokines that are released. Thanokines can elicit a broad array of responses in living cells, and we have demonstrated that Thanokines plays a previously unrecognized role in the pathogenesis of many important diseases. Our mission is to pioneer a novel category of drugs based on manipulating Thanokine Biology to treat cancer, immune and fibrotic diseases, and regenerative processes.
Inzen Therapeutics was founded by Flagship Pioneering, an organization dedicated to the origination and development of first-in-category life sciences companies. Since 2000, Flagship has originated and fostered the development of nearly 100 scientific ventures resulting in $20 billion in aggregate value, 500 issued patents, and more than 50 clinical trials for novel therapeutic agents.
Come join a dynamic and expanding team as a bioinformatician/computational biologist. We are exploring a new area of biology relating to cell death that requires us to develop creative analyses, integrating in-house and external omics data. This role will particularly appeal to someone who likes working on lots of different projects and has the skill set to flex among them rapidly. There will be ample opportunity to directly interact with biologists and present results that help drive decision making at Inzen. A successful candidate will enjoy a healthy mix of tool development, infrastructure building, and developing ad hoc analyses to advance Inzen’s core hypotheses by applying bioinformatic wizardry. We are specifically looking for candidates who have worked extensively with large scale, publicly available data sets in the oncology space (TCGA, CCLE, DepMap, etc.), immunology space, drug sensitivity / mechanism of action space (L1000), and other real world evidence. These data sources will be leveraged for indication selection and biomarker prediction to enable pre-clinical and clinical studies. The position reports to Inzen’s Head of Data Science and is located in Cambridge, MA.
- Work closely with Data Science, Platform, and Biology teams to create and execute appropriate data analysis plans.
- Identify, recommend, acquire, and wrangle relevant public and third-party ‘omics data and perform integrative data analyses to generate insights and propose therapeutic hypotheses.
- Perform integrative, pathway, and network analyses to understand disease mechanisms, determine clinical relevance, and for the discovery of biomarkers and important drug targets.
- Develop clear, intuitive visualizations. Communicate analysis results via presentations.
- Maintain documented records of analyses to facilitate reproducible research (markdown notebooks, computational environments, etc.) and convert repetitive analyses to pipelines.
- Author, document, and maintain computational tools as necessary to further Inzen’s analytical and data management goals.
- Monitor and evaluate new and emerging analytical technologies, and identify opportunities for collaboration within Flagship Pioneering companies, academia, and third-parties.
- Light management of SaaS products obtained by Inzen to enable data research.
- Ph.D. in bioinformatics, computational biology, biostatistics, biology or a related discipline. Prior research in applied oncology informatics strongly preferred.
- Minimum two years of experience working with large-scale biological transcriptomics, proteomics, human genetics, and other ‘omics datasets. Candidates with M.S. degree in above-named fields with extensive (at least 5-7 years) work experience will also be considered.
- Deep familiarity with structure and contents of large-scale public oncology omics data sets (e.g. TCGA, CCLE, DepMap) and a demonstrated ability to mine these data sets to generate or support scientific hypotheses
- Experienced and proficient with experimental design, data processing, statistical analysis, and bioinformatics analysis/reporting for genomics, proteomics, transcriptomics and/or metabolomics.
- Familiarity with development of regression models for high dimensionality data.
- Familiarity with SQL, data architecture engineering, ORMs, and query methods for REST APIs.
- Experience with software development best practices (e.g. git, unit testing, CI/CD) is a plus.
- Familiarity with public domain genomics transcriptomics, proteomic, and other ‘omics data sources outside of oncology applications is a plus. Public domain immunology data set knowledge is a strong plus.
- Hands-on experience with data visualization tools (ggplot, D3, R-Shiny, Spotfire, Google Charts, etc.) is a plus.
- Experience working within a cloud computing environment (AWS, GCP) is preferable.
- Motivated and team oriented, with an ability to thrive in an entrepreneurial and multidisciplinary environment.
- Excellent communication and presentation skills. Must be able to speak “biology” and “data science.” Must be able to think independently, work collaboratively and contribute to an active intellectual environment.
Inzen Therapeutics and Flagship Pioneering are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status.
Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.
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