Job Duties Leverage structured and unstructured data from various media and entertainment sources to prepare datasets for advanced analytics and modeling Develop and deliver impactful analytical tools and solutions leveraging statistical modeling machine learning and data science to uncover business insights and support strategic decision-making Design and apply advanced predictive and machine learning models including clustering K-means hierarchical classification KNN Naive Bayes CART time series forecasting logistic regression and econometric models to optimize pricing strategies assess price elasticity segment customers and enhance revenue across channels Leverage generative AI and large language models LLMs to develop and implement personalized content and messaging strategies across diverse media channels enhancing audience engagement and campaign effectiveness Assess and validate statistical models using appropriate performance metrics to ensure precision and accuracy such as accuracy sensitivity specificity ROC AUC Analyze consumer behavior trends and shifts across various digital touchpoints perform cross-channel attribution analysis to inform targeted retention strategies Monitor and analyze key engagement metrics to assess the performance of subscriber onboarding programs and their impact on long-term retention Interpret complex analytical insights and translate them into transparent actionable business strategies that improve business outcomes Support scalable deployment of data products by following best practices in CI CD processes and contribute to agile project management through tools like Jira for sprint planning tracking and team coordination Collaborate cross-functionally with technical and non-technical stakeholders to gather requirements define project scope and lead data science initiatives demonstrating strong communication leadership and team-building skills Responsibilities Job Duties Leverage structured and unstructured data from various media and entertainment sources to prepare datasets for advanced analytics and modeling Develop and deliver impactful analytical tools and solutions leveraging statistical modeling machine learning and data science to uncover business insights and support strategic decision-making Design and apply advanced predictive and machine learning models including clustering K-means hierarchical classification KNN Naive Bayes CART time series forecasting logistic regression and econometric models to optimize pricing strategies assess price elasticity segment customers and enhance revenue across channels Leverage generative AI and large language models LLMs to develop and implement personalized content and messaging strategies across diverse media channels enhancing audience engagement and campaign effectiveness Assess and validate statistical models using appropriate performance metrics to ensure precision and accuracy such as accuracy sensitivity specificity ROC AUC Analyze consumer behavior trends and shifts across various digital touchpoints perform cross-channel attribution analysis to inform targeted retention strategies Monitor and analyze key engagement metrics to assess the performance of subscriber onboarding programs and their impact on long-term retention Interpret complex analytical insights and translate them into clear actionable business strategies that improve business outcomes Support scalable deployment of data products by following best practices in CI CD processes and contribute to agile project management through tools like Jira for sprint planning tracking and team coordination Collaborate cross-functionally with technical and non-technical stakeholders to gather requirements define project scope and lead data science initiatives demonstrating strong communication leadership and team-building skills Qualifications Master s or PhD in data Science statistics computer science or related quantitative field 5 years experience in data science roles with demonstrated impact on retention engagement or churn reduction Advanced skills in Python R SQL and experience with ML libraries scikit-learn XGBoost TensorFlow PyTorch Strong background in building predictive churn models CLV causal inference and uplift modeling Leverage cloud platforms e g AWS Azure and big data tools e g Spark Hive Databricks staying current with evolving technologies and Databricks architecture for scalable data science workflows

📌 Assistant Manager-data Science-data Scientist (India)
🏢 EXL Service
📍 India