Led by Michael Antonov, a co-founder of Oculus, and well-funded by Formic Ventures, Deep Origin is poised to reinvent the way scientists work and life science innovations come to life. We envision a future largely free of diseases, where a 150-year lifespan becomes the norm. To achieve this, we are building an operating system for science, empowering scientists to be more productive and to bring tomorrow's ideas to life quickly and effectively.
The Product Manager / SME will lead our effort to develop and bring to market The DataHub, a pluginable data warehouse product designed for life sciences, with some ELN/LIMS capabilities. This product needs to be able to provide ways to capture, store and organize scientific data and support analysis. This may integrate with 3rd party software.
The purpose of this role is to
- Guide direction of DataHub development by identifying key unaddressed opportunities in the market at intersection of wet lab data, analysis and AI
- Guide decisions on key capabilities / product functionality we may need to develop for customer segments.
- Work closely with engineering to develop the product
- Work with cross-functional teams to bring the product to market
Requirements
- Experience working in a product management or solution engineering role at an ELM/LIMS vendor or experience with building and managing a lab software infrastructure for a sizable (50+ people) biotech or Pharma, including selecting ELN/LIMSs, building data integration.
- Experience and/or understanding of schemas for ELN/Lims data to reference different ontologies, biological entities etc
- Has deep knowledge of scientific lab workflows, i.e. how wet lab protocols are typically stored, managed and performed; where their results are stored and tracked; how are reagents and supplies tracked; how the resulting data is recorded, utilized for later computational analyst and reporting
- Has understanding of what kind of data needs to be extracted from LIMS for what kind of analysis
- Has experience with lab automation, including automated data capture and processing from instruments
- Has standardized and scaled protocols, that include wet lab and computational components, from research to reproducible/production
- A good understanding of industry players, their capabilities and competitive advantages and weaknesses
- A strong understanding of market needs and a vision for a solution.
- Preferably has written code/oversaw systems that extract data from LIMS/LabData systems and used it for bioinformatics or other statistical analysis
United States
