Require a Manager - Data and Analytics in Kolkata

Lead the end-to-end development and management of data analytics platforms and reporting systems within the financial services environment. Design and implement scalable data models, ETL pipelines, and dashboards to support real-time decision-making across business units. Spearhead advanced analytics projects including predictive modeling, customer segmentation, credit risk analysis, and fraud detection. Collaborate with cross-functional teams (Finance, Risk, Compliance, IT, Product) to identify business needs and deliver data solutions that drive performance. Establish and enforce data governance frameworks, ensuring data quality, consistency, and regulatory compliance (e.g., RBI guidelines, GDPR, KYC). Mentor and manage a team of data analysts and junior data scientists, fostering a culture of innovation, continuous learning, and high performance. Present key insights and strategic recommendations to senior leadership through executive-level reports and data storytelling. Stay ahead of emerging trends in financial analytics, AI/ML applications, and big data technologies to maintain a competitive edge. Ensure data security and privacy protocols are integrated into all analytics workflows and systems. RequirementsBachelors or Masters degree in Statistics, Mathematics, Computer Science, Economics, Finance, or a related quantitative field. 25 years of progressive experience in data analytics, business intelligence, or data science within the financial services industry. Proven experience managing data teams and leading analytics projects from conception to delivery. Expertise in SQL, Python/R, and data visualization tools (e.g., Tableau, Power BI, Looker). Strong understanding of financial products, risk assessment models, regulatory reporting, and compliance frameworks. Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is highly desirable. Familiarity with machine learning techniques and their application in fraud detection, credit scoring, and customer behavior prediction. Excellent communication, leadership, and stakeholder management skills with the ability to translate technical concepts for non-technical audiences. Ability to thrive in a fast-paced, evolving environment with a focus on innovation and operational excellence. Lead the end-to-end development and management of data analytics platforms and reporting systems within the financial services environment. Design and implement scalable data models, ETL pipelines, and dashboards to support real-time decision-making across business units. Spearhead advanced analytics projects including predictive modeling, customer segmentation, credit risk analysis, and fraud detection. Collaborate with cross-functional teams (Finance, Risk, Compliance, IT, Product) to identify business needs and deliver data solutions that drive performance. Establish and enforce data governance frameworks, ensuring data quality, consistency, and regulatory compliance (e.g., RBI guidelines, GDPR, KYC). Mentor and manage a team of data analysts and junior data scientists, fostering a culture of innovation, continuous learning, and high performance. Present key insights and strategic recommendations to senior leadership through executive-level reports and data storytelling. Stay ahead of emerging trends in financial analytics, AI/ML applications, and big data technologies to maintain a competitive edge. Ensure data security and privacy protocols are integrated into all analytics workflows and systems. RequirementsBachelors or Masters degree in Statistics, Mathematics, Computer Science, Economics, Finance, or a related quantitative field. 25 years of progressive experience in data analytics, business intelligence, or data science within the financial services industry. Proven experience managing data teams and leading analytics projects from conception to delivery. Expertise in SQL, Python/R, and data visualization tools (e.g., Tableau, Power BI, Looker). Strong understanding of financial products, risk assessment models, regulatory reporting, and compliance frameworks. Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is highly desirable. Familiarity with machine learning techniques and their application in fraud detection, credit scoring, and customer behavior prediction. Excellent communication, leadership, and stakeholder management skills with the ability to translate technical concepts for non-technical audiences. Ability to thrive in a fast-paced, evolving environment with a focus on innovation and operational excellence.