Decision Scientist, Health Economics and Decision Modeling

Bengaluru (On-site) | Full-time

BreathEasy flags cancer risk from a single breath. You will build the models that decide what should happen next for a patient who tests positive in the US, and what early detection is worth to patients and health systems.

About Dognosis

Dognosis digitizes canine cognition to detect 30+ human cancers from a single breath sample, with accuracy exceeding standard-of-care diagnostics and at a cost low enough to scale across entire populations. We are backed by top-tier VCs across India, the US, Israel, and Europe (including Accel India), have published in the Journal of Clinical Oncology, and collaborate with UCL, Narayana Health, and Medical Detection Dogs. We are pre-revenue, well-funded, and entering prospective clinical validation.

The Modeling Program

BreathEasy showed 90%+ sensitivity across six cancer types in Phase 2 and is now in prospective validation across multiple hospital sites in India. As we prepare for US market entry, you will work directly with Dr. Iakovos Toumazis, a member of our Scientific Advisory Board and an NCI-funded leader in cancer screening modeling, along with our US-based investigators. Your models turn test performance into the evidence clinicians, payers, and partners need.

What You Will Do

• Build decision-tree and Markov or microsimulation models to find the best imaging pathway after a positive test.
• Run cost-effectiveness analyses (QALYs, ICERs) with deterministic and probabilistic sensitivity analyses.
• Analyze data from cancer registries, nationally representative surveys, and clinical trials.
• Turn published literature and your own data analysis into well-sourced, defensible model inputs.
• Project population-level outcomes of BreathEasy: cancers caught earlier, lives saved, and costs avoided.
• Act as the statistical peer for our Science team, including improving our Bayesian detection model.

What Success Looks Like (6 Months)

• A validated imaging-pathway model, reviewed with Dr. Toumazis and ready to guide US strategy.
• A first cost-effectiveness analysis ready for a manuscript and for payer conversations.
• Science brings you in on study design and Bayesian modeling questions as a matter of course.

You Are a Good Fit If

• You hold a Master's in Biostatistics or a closely related quantitative field. A PhD is preferred.
• You have hands-on experience building decision trees, Markov models, or microsimulations, and know where their assumptions break.
• You have hands-on experience running a cost-effectiveness analysis end to end, sensitivity analyses included.
• You write clean, reproducible R or Python that someone else can rerun and audit.
• You write clearly for async review and work well with investigators across time zones.
• Valuable but Not Required
• Hands-on experience in cancer screening, early detection, or health technology assessment.
• Hands-on Bayesian modeling (Stan, PyMC, or similar).
• Peer-reviewed work in medical decision making or health economics.
• Learn more at dognosis.tech