Include the use of querying tools, reports and analyses to mitigate risk resulting from changes made to our decision engines.
Understand of how data is created, transformed, and used within and across business processes and ability to analyze and interpret huge volumes of data from multiple source for reconciliation purpose.
Work with Business/Stakeholders to gather the requirements, understand the business logic and define Data Quality rules/validation checks
Leverage a variety of analytical, technical and statistical applications (SAS, SQL, Python) to describe, analyze, and validate trends in large complex data sets. Ability to synthesize / analyze diverse information, develops recommendations, and makes decisions.
Identify and resolve concerns by assisting developers, project managers, technology leads, production support, business/underwriting, and Risk Strategy Stakeholders with inquiries.
Research production tickets/defects – including monitoring, reporting, and resolution with appropriate stakeholders, including identification of process improvement opportunities and automation
Build Detective Controls and data monitoring Reports to mitigate risk resulting from changes that impact Risk Decision Engines & Third party services
Support Outlier analysis and ad-hoc risk based analysis i.e. descriptive metrics, trend analysis, customer profiling, performance reporting, data monitoring, Build lineage controls, seasonality etc.
Lead and deliver on automation of reporting process using tools like SQL, VBA Coding, Tableau, Cognos and Alteryx
Assess potential end-user or customer impacts for Strategy changes. Liaise with business key stakeholders to ensure vendors have clear specifications for each project and/or initiative. Maintain the appropriate tracking and documentation for all consumption engagements, related processes, flows and functional documentation. Maintain appropriate Risk Control Self Assessments (RCSA’s) and business analysis/ requirements
Required qualifications, capabilities, and skills
Bachelor’s/Master’s degree in Engineering or Computer Science.
Strong Leadership, organizational skills, communication skills and the ability to work independently.
Strong SAS, SQL and python and/or other Oracle and/or Teradata database tools
Strong database knowledge and analytical skills
Proficient with Microsoft Office suite, particularly Excel and PowerPoint
Ability to work as part of a team
Capacity to work under time-sensitive business deadlines
Strong attention to detail. Excellent verbal and written communication skills and Capacity to work under time-sensitive business deadlines
Working knowledge of BI / data visualization tools like Tableau, QlikView, Power BI, Alteryx, etc. on the Big Data ecosystem
Knowledge of Data Quality Management/Tools. Experience with working in Agile framework and familiarity with data warehousing concepts and techniques.