Decision Scientist, Health Economics and Modeling Bengaluru · Full-time →

Dognosis; Bengaluru; Hybrid; INR 2.500.000 - 4.500.000; Vollzeit

Benefits dieser Stelle

Health insurance

Flexible hours

Work-from-home days

Gym allowance ₹10k/yr

Zusammenfassung

Dognosis in Bengaluru, India, is seeking a Decision Scientist for Health Economics and Modeling to advance CancerWatch through decision-tree, Markov, and microsimulation models. You will turn clinical and literature data into principled inputs that guide imaging pathways and payer conversations.

You will collaborate with the Science team and external investigators, perform full cost-effectiveness analyses (QALYs, ICERs) with sensitivity analyses, and contribute to Bayesian modelling as we scale

Qualifikationen

• Master's in Biostatistics or closely related quantitative field.
• Experience building decision trees, Markov models, or microsimulations.
• Experience running a cost-effectiveness analysis end to end with sensitivity analyses.
• Proficiency in clean, reproducible R or Python code.
• Ability to communicate clearly for asynchronous review across time zones.

Aufgaben

• Build decision-tree and Markov or microsimulation models to optimize imaging pathways after a positive test.
• Run cost-effectiveness analyses (QALYs, ICERs) with deterministic and probabilistic sensitivity analyses.
• Analyse cancer registry data, representative surveys, and clinical trials.
• Turn literature and own data into defensible model inputs.
• Project population-level outcomes and savings from CancerWatch.
• Serve as statistical peer for the Science team and improve Bayesian detection models.

Kenntnisse

Biostatistics

Decision trees

Markov models

Microsimulations

Cost-effectiveness analysis

R

Python

Clear written communication

Ausbildung

Master's in Biostatistics or related field

PhD preferred

Tools

R

Python

Jobbeschreibung

Decision Scientist, Health Economics and Modeling

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.

Dognosis is a deeptech company devoted to unleashing the superpowers of humanity's best friends. We build brain-computer interfaces, wearable sensors, robotic platforms and AI models to standardise, scale and augment canine olfaction. Our focus is a breath-based multi-cancer test that triages risk at population scale, so early cancer detection can reach everyone. Our mission is informed peace of mind for people and their companions, through interspecies technology that makes medicine truly proactive. We are based in Bengaluru, India, backed by Boost VC and 1517 Fund, selected for the Accel and Prosus Atoms X LeapTech cohort, and we work with healthcare and research institutions across India, the UK and the US.

We think from first principles, question the status quo, take responsibility, move fast and keep bureaucracy to a minimum. If you are new to startups, you may find the constant contact with reality, and the freedom to act on it, refreshing.

About the role

CancerWatch 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.

What you'll 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.
• Analyse 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 CancerWatch: cancers caught earlier, lives saved, and costs avoided.
• Act as the statistical peer for our Science team, including improving our Bayesian detection model.

What we look for

• 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.

Good to have

• Hands-on experience in cancer screening, early detection, or health technology assessment.
• Peer-reviewed work in medical decision making or health economics.

What success looks like

• 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 modelling questions as a matter of course.

The Modelling Programme

CancerWatch 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 modelling, along with our US-based investigators. Your models turn test performance into the evidence clinicians, payers, and partners need.

What you'll get

• Health insurance for you, through Plum.
• Flexible hours, and work-from-home days where the role allows.
• Up to ₹10,000 a year towards a gym, a sport or any regular fitness activity.