Data Scientist

As a Data Scientist at our company, your role will involve designing, validating, and deploying statistical models to drive business decisions. You will collaborate with cross-functional teams and external partners to identify future modeling opportunities. The ideal candidate should have hands-on experience in statistical analysis, predictive modeling, Python/R programming, SQL, data visualization, and model lifecycle management. Key Responsibilities: - Design, develop, and implement statistical and predictive models for various business use cases. - Build regression, clustering, time-series forecasting, risk scoring, and hypothesis-testing models. - Develop advanced analytical solutions including Matched Cohort Studies, Risk Modeling, Next Best Action Models, Customer Segmentation, and Predictive Analytics. - Perform feature engineering, model training, testing, and optimization. - Validate models using appropriate statistical techniques and performance metrics. - Monitor model performance, drift, bias, and stability in production environments. - Provide technical leadership and guidance to external vendors and analytics partners. - Translate business requirements into analytical solutions. - Present complex analytical findings to business stakeholders in a transparent and actionable manner. - Extract, clean, transform, and analyze large datasets using SQL and Python/R. - Collaborate with Data Engineering teams to build scalable analytical solutions. - Identify opportunities for advanced analytics and machine learning across the organization. - Research and evaluate emerging statistical and machine learning techniques. - Contribute to analytics best practices and data science strategy. This job as a Data Scientist also involves working with structured and unstructured data from multiple sources and collaborating on innovative solutions with the Data Engineering team. As a Data Scientist at our company, your role will involve designing, validating, and deploying statistical models to drive business decisions. You will collaborate with cross-functional teams and external partners to identify future modeling opportunities. The ideal candidate should have hands-on experience in statistical analysis, predictive modeling, Python/R programming, SQL, data visualization, and model lifecycle management. Key Responsibilities: - Design, develop, and implement statistical and predictive models for various business use cases. - Build regression, clustering, time-series forecasting, risk scoring, and hypothesis-testing models. - Develop advanced analytical solutions including Matched Cohort Studies, Risk Modeling, Next Best Action Models, Customer Segmentation, and Predictive Analytics. - Perform feature engineering, model training, testing, and optimization. - Validate models using appropriate statistical techniques and performance metrics. - Monitor model performance, drift, bias, and stability in production environments. - Provide technical leadership and guidance to external vendors and analytics partners. - Translate business requirements into analytical solutions. - Present complex analytical findings to business stakeholders in a transparent and actionable manner. - Extract, clean, transform, and analyze large datasets using SQL and Python/R. - Collaborate with Data Engineering teams to build scalable analytical solutions. - Identify opportunities for advanced analytics and machine learning across the organization. - Research and evaluate emerging statistical and machine learning techniques. - Contribute to analytics best practices and data science strategy. This job as a Data Scientist also involves working with structured and unstructured data from multiple sources and collaborating on innovative solutions with the Data Engineering team.