S&C Global Network AI FS Data Management Specialist

Key Responsibilities:

• Data Management and Governance:
• Oversee the data management strategy for financial services within the global network to ensure data quality, consistency, and compliance across multiple regions.
• Implement data governance policies to ensure adherence to regulatory requirements (e.g., GDPR, CCPA, SOX) and best practices.
• Develop data models and workflows that meet the business requirements while ensuring data security and privacy.
• AI and Machine Learning Implementation:
• Work closely with AI/ML teams to build intelligent data systems, utilizing artificial intelligence and machine learning techniques to improve data quality, predictive analytics, and decision-making processes.
• Implement machine learning algorithms to automate data categorization, anomaly detection, and risk assessments within financial data systems.
• Integrate AI-powered tools with data lakes and cloud storage systems to enhance the analysis of large datasets in real-time.
• Data Integration and Architecture:
• Design and implement data integration frameworks that connect diverse data sources (e.g., transactional data, customer insights, financial records) across the S&C Global Network.
• Create an enterprise data architecture that supports efficient, scalable, and secure data flows across platforms (on-premise and cloud-based).
• Ensure seamless data pipeline integration using technologies such as ETL (Extract, Transform, Load), APIs, and real-time data streaming.
• Data Analytics and Reporting:
• Collaborate with data analysts and business intelligence teams to develop insights that drive business decisions within financial services.
• Provide actionable data insights through AI-driven analytics, enabling stakeholders to make informed decisions.
• Utilize data visualization tools (e.g., Power BI, Tableau) to create reports and dashboards for senior leadership, identifying trends, patterns, and potential risks.
• Financial Services (FS) Data Strategy:
• Develop and maintain a strategic roadmap for financial services data across the S&C Global Network, aligning with business goals and IT objectives.
• Work with cross-functional teams to improve the data lifecycle management process from data collection and storage to analysis and reporting.
• Enhance the ability to track and manage financial data systems, ensuring accuracy and completeness in reporting, auditing, and regulatory compliance.
• Collaboration and Stakeholder Management:
• Work closely with business stakeholders, including senior leaders, to understand requirements and propose solutions that address data challenges within global financial networks.
• Lead cross-functional teams to implement data-driven solutions, fostering collaboration between business, technology, and data teams.
• Provide training and support to teams on the effective use of AI-powered data management tools and data governance processes.
• Continuous Improvement and Innovation:
• Stay current with AI trends, data management best practices, and innovations in financial services data technologies.
• Propose and implement new technologies or processes that can improve data management efficiency, scalability, or automation.
• Develop a culture of continuous improvement in data quality and AI-powered decision-making within the organization.

Requirements:

• Education:
• Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, Financial Services, or related fields.
• Relevant certifications in AI/ML, Data Management, or Financial Services are a plus.
• Experience:
• 5+ years of experience in data management, AI/ML applications, and financial services.
• Proven track record of managing large-scale data projects within global networks.
• Hands-on experience with AI-powered data systems, predictive analytics, and data pipelines.
• Expertise in financial data management, including compliance, reporting, and risk management processes.
• Technical Skills:
• Strong knowledge of data integration tools (e.g., ETL, API integration, streaming data).
• Experience with AI frameworks (e.g., TensorFlow, PyTorch, Azure AI).
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud for data storage and computing.
• Advanced proficiency in SQL and experience with big data technologies (e.g., Hadoop, Spark, Databricks).
• Proficient in data visualization tools such as Power BI, Tableau, or similar.
•