Position Overview
We are seeking a skilled Modeler to contribute to the development and optimization of marketing analytics models. You will work within a cross-functional team to build propensity models, next-best-action (NBA) engines, customer segmentation frameworks, and campaign response models that power data-driven marketing strategies. You will apply best practices in model explainability, fairness testing, and lifecycle governance to ensure high-quality, compliant model outputs.
Key Responsibilities
- Develop and optimize propensity models, segmentation frameworks, and campaign response models using supervised and unsupervised machine learning techniques.
- Conduct bias testing and implement model explainability methods (e.g., SHAP, LIME) to support model approval and governance workflows.
- Perform exploratory data analysis and feature engineering to identify meaningful predictors of customer behavior.
- Support the full model lifecycle including development, documentation, validation support, performance monitoring, and periodic re-validation.
- Collaborate with marketing and data teams to understand business objectives and translate them into modeling requirements.
- Prepare explicit, concise model documentation including methodology overviews, performance summaries, and limitation disclosures.
- Monitor deployed models for data drift, performance degradation, and champion-challenger evaluation.
- Contribute to A/B test design and campaign measurement analyses to evaluate marketing effectiveness.
- Stay current on advances in marketing data science, uplift modeling, and customer analytics.
Qualifications & Experience
- 3–6 years of experience in data science, analytics, or quantitative modeling with a focus on customer or marketing analytics.
- Hands-on experience building and evaluating classification and regression models for propensity scoring or segmentation.
- Proficiency in Python with working knowledge of libraries such as scikit-learn, XGBoost, Li
📌 Data Scientist (Gurugram)
🏢 EXL
📍 Gurugram