DECISION SCIENCE MANAGER

As a Decision Science Manager RCAS - Analytics at HSBC, you play a crucial role in leveraging data and analytics capabilities to drive smarter decisions and profitable growth across various domains. Your responsibilities will include: - Supporting business groups by conducting data analysis, developing models and strategies, implementing Business Intelligence, and managing data. - Addressing a range of business problems such as business growth, customer experience enhancement, risk exposure limitation, capital quantification, and internal processes improvement. - Establishing GSC capability to support Analytics and Automation activities. Additionally, you are responsible for: - Executing data analytics in line with the Risk Management Framework requirements. - Delivering repeatable and scalable analytics through semi-automation of L1 Financial Crime Risk and Regulatory Compliance Risk Assurance controls testing. - Collaborating in cross-functional projects to discover insights for strategic decisions and optimization opportunities using advanced data modeling and analysis techniques. Moreover, you contribute to: - Building, developing, and maintaining reporting systems, data automation systems, dashboards, and performance metrics to support key business decisions. - Designing and delivering reports and insights that analyze business functions, key operations, and performance metrics. - Ensuring that analytics work meets CA standards and complies with the Group Standards Manual and Compliance FIM. Qualifications required for this role: - Masters degree with 3-4 years of overall industry experience or bachelors degree with 4-5 years of industry experience in statistics, economics, or any other quantitative field. - Minimum 3 years of hands-on analytics experience in solving complex business problems using data. - Strong analytical skills with business analysis experience and a deep understanding of financial services/banking operations. - Proficiency in Python Streamlit/Flask/Django and other Data Science Tools. - Experience in visualization tools like QlikSense/Tableau/PowerBI and website development technologies. - Proficiency in process documentation, version management, and knowledge of tools like GitHub, JIRA. - Familiarity with AI/ML space, data engineering skills, cloud technologies (GCP, AWS, Azure), and Dev-Ops tools.,