Key Responsibilities
- Design, build, and maintain statistical MMM models to quantify ROI across channels (HCP engagement, DTC, digital, field force, etc.).
- Analyze impact of promotions, pricing, seasonality, payer dynamics, and regulatory constraints on product performance.
- Translate complex model outputs into clear business insights and actionable recommendations for senior stakeholders.
- Collaborate with MMM lead in the team to align MMM with business strategy.
- Handle multi-country / multi-brand datasets, ensuring consistency in modeling frameworks across geographies.
- Integrate omnichannel data sources (CRM, media spend, claims, prescriptions, digital engagement, etc.).
- Conduct scenario planning and optimization to guide marketing allocation and budget decisions.
- Continuously improve MMM methodologies by incorporating advanced analytics techniques (Bayesian models,



causal inference).

Required Qualifications
- 6+ years of experience in Marketing Mix Modeling analytics.
- Hands-on experience in Healthcare, Pharma, or Medical Devices industry (mandatory).
- Robust expertise in regression modeling, time-series analysis, and causal inference.
- Proficiency in Python/R (statsmodels, PyMC, Prophet, scikit-learn, etc.).
- Experience working with large-scale, messy datasets (claims, prescription, healthcare provider data).
- Deep understanding of healthcare marketing channels (HCP promotion, field force, digital, patient marketing).
- Proven ability to present complex insights to non-technical business stakeholders.

📌 Marketing Mix Modeling (India)
🏢 BayOne Solutions
📍 India