Associate Divisional Manager-Data Analytics

Role Overview: As an Associate Divisional Manager - Data Analytics (Data Science) at our organization, your main responsibility will be to manage and lead a team of 4-5 data scientists. Your focus will be on developing predictive modeling solutions specifically in the areas of credit risk and marketing for both Consumer and Commercial lending portfolios. Key Responsibilities: - Provide insights and conduct trend and variance analyses across the product suite to support cross-sell activities from a risk and marketing perspective. - Assist Business teams in analyzing the root cause of trends, identifying incremental sales opportunities, and exploring risk mitigation avenues. - Develop machine learning models, segmentation strategies, and provide mentorship to junior analysts on developing solutions that integrate business requirements and operational limitations. - Ensure the implementation of operationally efficient solutions and drive optimization in existing analytics solutions. Qualification Required: - M.Tech / B.E / B.Tech / M.Sc in Computer Science, Statistics, or Mathematics. - Preferably 8+ years of experience in data science with expertise in Statistical/ Machine learning / Deep Learning Models. - Proficient in SQL and Python with hands-on experience in risk analytics, credit risk models, marketing analytics, marketing models, portfolio monitoring, and Expected credit loss (ECL) models. Additional Details: You should possess excellent analytical, logical, problem-solving, and numerical skills. Familiarity with Python, SQL, and advanced Excel skills will be crucial for success in this role. Moreover, your experience in credit risk models, marketing analytics, marketing models, and portfolio monitoring will be highly valued. Familiarity with lending products such as personal loans, consumer loans, credit cards, tractor loans, and commercial vehicle loans is preferred. Additionally, expertise in XG Boost, Logistic Regression, Deep Learning, underwriting strategy development, Acquisition Risk Scorecard, Behaviour Risk Scorecard, Propensity Models, and CHAID segmentation will be beneficial. Experience working with Indian Banks/ NBFC will be an advantage. Role Overview: As an Associate Divisional Manager - Data Analytics (Data Science) at our organization, your main responsibility will be to manage and lead a team of 4-5 data scientists. Your focus will be on developing predictive modeling solutions specifically in the areas of credit risk and marketing for both Consumer and Commercial lending portfolios. Key Responsibilities: - Provide insights and conduct trend and variance analyses across the product suite to support cross-sell activities from a risk and marketing perspective. - Assist Business teams in analyzing the root cause of trends, identifying incremental sales opportunities, and exploring risk mitigation avenues. - Develop machine learning models, segmentation strategies, and provide mentorship to junior analysts on developing solutions that integrate business requirements and operational limitations. - Ensure the implementation of operationally efficient solutions and drive optimization in existing analytics solutions. Qualification Required: - M.Tech / B.E / B.Tech / M.Sc in Computer Science, Statistics, or Mathematics. - Preferably 8+ years of experience in data science with expertise in Statistical/ Machine learning / Deep Learning Models. - Proficient in SQL and Python with hands-on experience in risk analytics, credit risk models, marketing analytics, marketing models, portfolio monitoring, and Expected credit loss (ECL) models. Additional Details: You should possess excellent analytical, logical, problem-solving, and numerical skills. Familiarity with Python, SQL, and advanced Excel skills will be crucial for success in this role. Moreover, your experience in credit risk models, marketing analytics, marketing models, and portfolio monitoring will be highly valued. Familiarity with lending products such as personal loans, consumer loans, credit cards, tractor loans, and commercial vehicle loans is preferred. Additionally, expertise in XG Boost, Logistic Regression, Deep Learning, underwriting strategy development, Acquisition Risk Scorecard, Behaviour Risk Scorecard, Propensity Models, and CHAID segmentation will be beneficial. Experience working with Indian Banks/ NBFC will be an advantage.