SciPro Inc.
SciPro has partnered with a high-growth cloud-based healthtech company at the forefront of digital transformation in life sciences, seeking a Data Architect. With deep integration across the worlds leading cloud and AI platforms, this company is redefining how scientific organizations collect, structure, and activate their R&D data to power next-generation discovery.
They are looking for a Data Architect to collaborate directly with scientific stakeholders and internal cross-functional teams to deliver complex, data-centric solutions across the biopharma ecosystem. This role is key to translating lab-based workflows into scalable digital solutions, driving implementation of scientific data pipelines, and accelerating customers ability to leverage AI-ready data. This role is located in Boston, New York City, or San Fransisco.
Responsibilities
Translate lab workflows and scientific use cases into data-driven solutions using the companys proprietary platform Develop and implement technical components including Python-based data parsing, structured data design (JSON schemas), and lab software integration via APIs Create interactive visualizations using Python (Jupyter, Streamlit, hvPlot, etc.) or commercial BI tools (PowerBI, Tableau, Spotfire) Conduct detailed interviews with customer teams to gather business and scientific requirements Work cross-functionally with customer stakeholders and internal teams to ensure delivery of fit-for-purpose solutions Lead account sprint planning, manage delivery milestones, and communicate progress through customer demos and updates Identify reusable solution components to inform future product development Serve as a technical and scientific thought partner to customers, enabling long-term platform adoption and impact Main Qualifications
7+ years (PhD) or 10+ years (Masters) of hands-on experience using Python for data analysis, automation, or scientific data engineering 3+ years of experience in the life sciences domain (biotech, pharma, bioinformatics, or scientific software vendor) Strong ability to translate complex scientific needs into technical specifications and data architectures Experience integrating ELNs, LIMS, or other lab systems via APIs Excellent communication, critical thinking, and problem-solving skills with a collaborative mindset Strong customer orientation and the ability to manage delivery independently in a fast-paced environment Familiarity with cloud technologies (AWS, Azure, GCP) is a plus
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Translate lab workflows and scientific use cases into data-driven solutions using the companys proprietary platform Develop and implement technical components including Python-based data parsing, structured data design (JSON schemas), and lab software integration via APIs Create interactive visualizations using Python (Jupyter, Streamlit, hvPlot, etc.) or commercial BI tools (PowerBI, Tableau, Spotfire) Conduct detailed interviews with customer teams to gather business and scientific requirements Work cross-functionally with customer stakeholders and internal teams to ensure delivery of fit-for-purpose solutions Lead account sprint planning, manage delivery milestones, and communicate progress through customer demos and updates Identify reusable solution components to inform future product development Serve as a technical and scientific thought partner to customers, enabling long-term platform adoption and impact Main Qualifications
7+ years (PhD) or 10+ years (Masters) of hands-on experience using Python for data analysis, automation, or scientific data engineering 3+ years of experience in the life sciences domain (biotech, pharma, bioinformatics, or scientific software vendor) Strong ability to translate complex scientific needs into technical specifications and data architectures Experience integrating ELNs, LIMS, or other lab systems via APIs Excellent communication, critical thinking, and problem-solving skills with a collaborative mindset Strong customer orientation and the ability to manage delivery independently in a fast-paced environment Familiarity with cloud technologies (AWS, Azure, GCP) is a plus
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