Insilico Search Partners

Scientific Data Architect — Indianapolis, IN 📍 Indianapolis, IN | Full-Time | Hybrid

The Role We're looking for a product-minded, outcome-obsessed Scientific Data Architect to join a high-impact team at the intersection of life sciences R&D and AI. You'll work directly with scientific and technical stakeholders onsite a few days per week in the Indianapolis area, translating complex scientific data challenges into scalable, AI-ready solutions.

What You'll Do

• Design and implement extensible, reusable data models (tabular and JSON) that capture and organize scientific data at scale
• Develop Python-based parsers to programmatically interrogate proprietary instrument output files
• Integrate lab software (ELN/LIMS) via APIs and build data visualization apps using Streamlit, Plotly, and similar frameworks
• Collaborate with scientists, engineers, and product managers to develop and deploy ML, AI, and statistical models
• Rapidly prototype and demo solutions directly with end users to accelerate adoption
• Contribute to product roadmap by translating customer pain points into actionable priorities
• Travel to client sites in the Indianapolis, St. Louis, and Chicago regions as needed

What We're Looking For

• PhD with 4+ years or MS with 8+ years of industry experience in life sciences
• Deep domain knowledge in drug discovery, preclinical development, CMC, or product quality testing
• Proven track record designing and implementing AI/ML-driven use cases in cloud environments
• Hands-on Python development experience including data modeling, parsing, and app development
• Experience integrating ELN/LIMS systems via APIs
• Strong communication and storytelling skills — comfortable engaging scientists and executive stakeholders alike
• Self-starter mentality with a bias toward prototyping and action

Bonus Points

• Experience with Streamlit, Plotly, Holoviews, or similar data app frameworks
• Familiarity with AWS or other cloud-native environments
• Background in scientific consulting or customer-facing roles
• Experience with exploratory data analysis across complex biopharma datasets