Data Scientist- CSA (Mumbai)

Build and maintain lead scoring models to prioritize high-intent customers/prospects for sales and marketing teams Develop churn prediction models to identify at-risk customers and support retention strategies Design and execute Media Mix Modeling (MMM) studies to measure channel-level marketing effectiveness and guide budget allocation Write efficient SQL queries to extract, transform, and validate data from large marketing and transactional datasets Build and productionize data pipelines and models in Python (pandas, scikit-learn, statsmodels, or equivalent) Work within Google Cloud Platform (GCP) BigQuery, Cloud Run/Functions, IAM, and related services to build scalable data workflows Translate model outputs into explicit, business-relevant recommendations for marketing and media teams Collaborate with client servicing, media planning, and analytics teams to embed data science outputs into campaign and business decisions Stay current on marketing measurement approaches (attribution, incrementality, media effectiveness) and apply them to client problems Required Skills & Experience: Strong proficiency in Python for data analysis and machine learning Solid SQL skills, comfortable working with large, complex datasets Working knowledge of GCP, particularly BigQuery; familiarity with cloud-based data pipelines Practical experience building lead scoring and churn prediction models Experience with or solid conceptual understanding of Media Mix Modeling (e.g., adstock, saturation curves, Bayesian approaches such as Meridian, Robyn, .