The candidate will be responsible for building Data Quality controls, gathering requirements, supporting data profiling and threshold analysis primarily for Risk Decision Engines and Third-party services within Consumer & Community Banking. The candidate will be expected to have a detailed understanding of data quality, systems and statistical techniques. The candidate is will also be responsible for data monitoring and reporting and supporting post implementation validations during releases for any changes made to decision engines to ensure accuracy of decisioning and support root cause analysis in case of production issues or defects.
A balance of initiative, leadership, influence, and matrixed management skills are important success factors for this role. The right candidate will be comfortable working independently or as part of small project teams. She/he has strong analytical skills, is highly confident and possesses strong communication skills.
This is a critical role and will require both technical, statistical and analytical skills and the ability to engage with stakeholders.
Responsibilities:
Include the use of querying tools, reports, and analyses to mitigate risk resulting from changes made to our decision engines.
Understanding 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 sources 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 decision
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
Supporting 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.
Process Automation - Be able to lead and deliver on automation of reporting process using tools like SQL, VBA Coding, Tableau, python, pyspark 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
Post-implementation validations related to strategy changes tied to Decision Engines
System analysis and ongoing validation of core attributes
Maintain appropriate Risk Control Self Assessments (RCSA’s) and business analysis/ requirements
Qualifications
- Bachelor’s/Master’s degree in Engineering or Computer Science with 7-8 years experience in data analytics & Reporting
- 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
- UNIX experience preferred.
- Capacity to work under time-sensitive business deadlines
- Strong attention to detail & experience is statistical techniques
- Ability to work as part of a team
- 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 is preferred
- Experience in AWS cloud technologies and Databricks
- Experience with working in Agile framework and familiarity with data warehousing concepts and techniques.