Senior Data Scientist – Marketing Mix Modeling (MMM)
INR 3000K-5000K (estimate) Senior-level Full Time
Tasks
- Build Bayesian regression models
- Build constrained nonlinear optimization for marketing allocation
- Create Monte Carlo uncertainty propagation frameworks
- Design causal inference frameworks using quasi experimental methods
- Design marketing mix models using Bayesian methods
- Develop probabilistic models with PyMC or Stan
- Develop production quality Python modeling workflows
- Document modeling methodology and validation
- Estimate media effectiveness using adstock and saturation functions
- Implement hierarchical Bayesian models
- Implement multi objective optimization for ROI and constraints
- Mentor junior data scientists
- Perform Bayesian diagnostics and posterior analysis
Perks/Benefits
- N/A
Skills/Tech-stack
Adstock | ArviZ | Bayesian Change Point Models | Causal Inference | Change Point | Change point detection | Constrained Nonlinear Optimization | Cvxpy | Difference-in-differences | Forecasting | Geo-experiments | Geometric Adstock | Git | Hamiltonian Monte Carlo | Hill Functions | Hypothesis Testing | MCMC | Marketing Mix | Marketing Mix Modeling | Mix Modeling | Model Evaluation | Monte Carlo | Multi-Objective Optimization | NUTS | Nonlinear Optimization | NumPy | Objective optimization | Optimization | Pandas | Piecewise regression | Probability Distributions | Pymc | Python | Regression Analysis | Regression discontinuity | SQL | Saturation Curves | SciPy | SciPy Optimize | Scikit-learn | Series modeling | Stan | Synthetic control | Time Series | Time Series Modeling | Weibull Adstock
Education
Roles
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