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KEY RESPONSIBILITIES Define the roadmap for a high quality database in • Define and establish firm-wide data quality standards and processes to manage a large scale global database
• Review current QA procedures, suggest improvements and develop new systems to support ’s growing business needs
• Identify differences in database management across offices and define practices that align all offices to a single approach that is consistent and meets global standards
• Develop a data retention policy which is compliant with international data protection standards
• Incorporate timely/annual revisions to policies to ensure they are always up to date and aligned to the firm’s ‘current’ needs
• Define the escalation matrix to report QA issues
• As required, benchmark our data quality practices with best in class firms in the industry
• Provide input to any suggested changes in the database, or evaluation of new information management systems, from the point of view of anticipated QA concerns
• Have worked on codes and databases, ensuring consistency, completeness, correctness and the associated training, checking and corrections required.
• Must be familiar with reviewing of codes and building a regular review process to ensure codes meet current business needs Measurement - Auditing and Control
• Develop internal audit plans and ensure implementation. Own and supervise the internal audits across all levels/offices
• Develop, implement and review outcomes from corrective action plans of internal audits
• Lead investigations into serious quality issues and report to the senior stakeholders – Office Leaders, Heads of Research, etc
• Define the set of MIS/reports on QA that need to be shared with offices – what, with whom and how often
• Provide assistance and feedback to colleagues in regards to QA compliance and other QA issues
• Define appropriate technology interventions to identify QA gaps and resolve issues in a timely manner Execution
• Map the flow of information across global database, and identify the business critical data attributes upon which to focus resources and energy to gain the maximum return.
• Define appropriate levels of ownership for different elements affecting data quality, both centrally and at the local office level, ensuring the right balance
• Draw up an exhaustive list of QA errors and classify them as high, medium, low based on ‘impact’ on business
• Define turnaround times for each level of error, making sure they are identified and addressed in the most efficient and effective manner
• Ensure corrections are carried out in a timely manner, whether at local or central level
• Effectively use and leverage technology to build a robust information system – user friendliness, data capture, retrieval, sharing and reporting
• Ensure timely training and development (up-skilling as well) of all DQ team members
• Stay in close touch with all offices, support groups, Global Operations and Global Trainers to ensure alignment of goals and interventions related to database management
• Ensure proper training prior to the rollout of any new processes/systems
Communication, Training and Advice
• Ensure that all policies and procedures pertaining to QA are well understood across user groups
• Communicate any changes to existing practices, SOPs or even new processes, etc in a timely manner
• Implement the necessary training initiatives to make sure all are aligned to the needs/expectations
• Provide advice and assistance to all users on QA issues as required. Hold conference calls, etc with smaller focus groups to share key messages/updates/red flags
• Promote quality achievements and performance improvements throughout the firm - office and individual level
Staff Management
• Manage and motivate staff in Quality Assurance across the firm. This would include a team of centralized resources as well as a network of office-based resources with clearly defined responsibilities and goals.
• Create a positive climate that attracts, retains and motivates top performing staff. Recruit, train and reward staff in accordance with best practice requirements.
• Play an active role in the hiring process for local office DQ staff.
• Ensure proper staffing and capability of the centralized data quality team, as well as the office level
PERSONAL SKILLS:
• Must have a passion for data management
• Must be motivated, proactive and resourceful
• Excellent verbal and written communications skills
• Fluency in English both spoken and written is a must
• Good with analysing, researching and facilitating solutions
• Be engaging and have a strong partnering approach (consensus building where necessary)
• Problem solving approach
• Demonstrates clear leadership and direction in a challenging environment
• Seeks to deploy consistent methodologies and techniques
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