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Tier-1 pharma brand and metro Hyderabad increase density, but niche pharmacometrics specialization moderates applicants.
Strong domain specialization in pharmacometrics, PBPK, and translational modeling limits cross-industry transferability.
Explicit advanced-degree plus multi-year pharmacometrics and mechanistic-modeling requirements increase filtering stringency.
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Develop and apply mechanistic models (PBPK, TMDD, PK/PD, exposure-response) for biologics discovery and translational pharmacology questions.
Design and execute reproducible modeling workflows including parameter estimation, model calibration, sensitivity and uncertainty analysis to support data-driven decision-making.
Collaborate cross-functionally with translational scientists, pharmacology experts, and discovery teams to translate quantitative insights into actionable recommendations and support scalable drug design frameworks.
Doctorate degree plus 4+ years experience in Pharmacometrics, Quantitative Pharmacology, Pharmacokinetics, Bioengineering, Computational Biology, Applied Mathematics, Statistics, Data Science, or related field; OR Master's degree with 8+ years relevant experience.
Experience in developing PBPK, TMDD, PK/PD, exposure-response, or mechanistic models, particularly for biologics or therapeutic discovery.
Proficiency with scientific computing and modeling tools such as R, Python, MATLAB, NONMEM, Monolix, mrgsolve, Stan, PyMC, or SimBiology.
Work Experience Required: 4+ years with Doctorate or 8+ years with Master's, in relevant domains as above. Notice period: Not explicitly mentioned in the JD.
Brings deep domain expertise in biologics pharmacology, including target-mediated drug disposition and translational scaling across species.
Experienced in working within data-governed environments handling scientific, preclinical, or translational data for modeling purposes.
Skilled in developing reproducible scientific computing workflows with strong communication abilities to convey complex modeling assumptions, uncertainties, and recommendations to diverse scientific stakeholders.