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About the role
As part of the DQ Monitoring and Analytics team in Finance & Treasury, you will play a crucial role in implementing Technical Solutions for Data Quality and Analytics strategy. Your responsibilities will include: - Implementing standardisation in managing, monitoring, and tracking Data Quality (DQ) issues across Finance & Treasury Processes. - Contributing towards creating a data analytics capability to centralise and analyse adjustments, data quality exceptions, and providing insight into inconsistencies for resolution. - Providing expert data quality and analytics capability to identify and correlate DQ issues across Finance into common root cause and resolution. - Developing real-time technical use cases to improve control weaknesses and assisting the technology team in implementing them. - Identifying changes, recommending, and prioritizing them appropriately for creating efficiency within projects. You will work with technology and business stakeholders to produce a clear data profiling, data analytics, and MI strategy across Finance and Treasury. Additionally, you will establish a cross-cutting DQ platform, work closely with upstream business functions to validate DQ issues, and collaborate with Risk to understand and correlate DQ controls. Your role will also involve providing process teams with self-service capability and training for data analysis, identifying and mitigating risks related to F&T Data Quality, and contributing to DQ Governance forums for relevant Finance and Treasury Processes. In terms of skills and experience, you should possess expertise in: - Data modelling processes, machine learning algorithms, and predictive models - Extracting data from multiple sources like Relational Databases and Bigdata - Advanced Python Scripting, SQL, and Analytics Tools - Knowledge of Cloud Platforms such as Azure and AWS - Agile Methodology and BI Tools like Tableau and Power BI - Advanced SQL Queries and Database performance tuning - Source Code Control, Python scripting, and Data Quality tools like Informatica Data Quality Qualifications: - Graduate (Engineering/ Mathematics/ Economics/ Science) / MBA, PG Diploma in Banking / Finance / Statistics or related field - Certifications in Data Quality tools or Data Science would be an added advantage About the company: Standard Chartered is an international bank dedicated to making a positive difference for clients, communities, and employees. With a focus on driving commerce and prosperity through diversity, the bank encourages a culture of continuous improvement, innovation, and inclusion. If you are passionate about working for a purpose-driven organization and contributing to meaningful change, Standard Chartered welcomes your unique talents and values your individual growth. As part of the DQ Monitoring and Analytics team in Finance & Treasury, you will play a crucial role in implementing Technical Solutions for Data Quality and Analytics strategy. Your responsibilities will include: - Implementing standardisation in managing, monitoring, and tracking Data Quality (DQ) issues across Finance & Treasury Processes. - Contributing towards creating a data analytics capability to centralise and analyse adjustments, data quality exceptions, and providing insight into inconsistencies for resolution. - Providing expert data quality and analytics capability to identify and correlate DQ issues across Finance into common root cause and resolution. - Developing real-time technical use cases to improve control weaknesses and assisting the technology team in implementing them. - Identifying changes, recommending, and prioritizing them appropriately for creating efficiency within projects. You will work with technology and business stakeholders to produce a clear data profiling, data analytics, and MI strategy across Finance and Treasury. Additionally, you will establish a cross-cutting DQ platform, work closely with upstream business functions to validate DQ issues, and collaborate with Risk to understand and correlate DQ controls. Your role will also involve providing process teams with self-service capability and training for data analysis, identifying and mitigating risks related to F&T Data Quality, and contributing to DQ Governance forums for relevant Finance and Treasury Processes. In terms of skills and experience, you should possess expertise in: - Data modelling processes, machine learning algorithms, and predictive models - Extracting data from multiple sources like Relational Databases and Bigdata - Advanced Python Scripting, SQL, and Analytics Tools - Knowledge of Cloud Platforms such as Azure and AWS - Agile Methodology and BI Tools like Tableau and Power BI - Advanced SQL Queries and Database performance tuning - Source Code Control, Python scripting, and Data Quality tools like Informatica Data Quality Qualifications: - Graduate (Engineering/ Mathematics/ Economics/ Science) / MBA, PG Diploma in Banking / Finance / Statistics or related f
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