With rich experience applying cutting edge data methodologies to the biopharma R&D domain, you bridge understanding between present-day pain points and generalizable solutions.

You are an insatiable learner, with a track record of deeply learning new tools, methods, and domains.

You fundamentally embody the principles of extreme ownership and have a demonstrated history of building extensible data models and applications for Biopharma end users to maximize value from their data via analysis and integration with AI/ML.

This role will require extreme self-discipline and determination as we forge a category that will fundamentally and forever change the life science industry.

What You Have Done

• PhD with +4 years or Masters with +8 years of industry experience in life sciences  with extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing.
• Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments
• Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
• Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible.
• Engaged diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities.
• Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.

Requirements

What You Will Do

• You will be a critical team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite a couple of days per week in the Indianapolis area, building strong relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions.

• Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.

• Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.

• Own, scope, prototype, and implement solutions including:

• Data model design (tabular & JSON)

• Python-based parser development.

• Lab software (e.g., ELN/LIMS) integration via APIs.

• Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly) 

• Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)

• Programmatically interrogating proprietary instrument output files.

• Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings

• Proactively communicate implementation progress and deliver demos to customer stakeholders.

• Collaborate with the product team to build and prioritize our roadmap by understanding customers’ pain points within and outside Tetra Data Platform.

• Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases

• Must be able to travel to client sites in St.Louis, Indianapolis, Chicago regions.

Benefits

• Competitive Salary and equity in a fast-growing company.
• Supportive, team-oriented culture of continuous improvement.
• Generous paid time off (PTO).
• Flexible working arrangements - Remote work when not at Customer Sites

We are not currently providing visa sponsorship for this position.

Apply

Apply at TetraScience

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