DVP - Model Risk Audit & Data Analytics - Financial Services

About this Opportunity:

We are looking for an DVP - Model Risk Auditor and Data Analytics Lead to join the Internal Audit & Advisory Department, who will be responsible for auditing/reviewing all aspects of Model Risk Management from model risk governance and control, independent model validation to model performance monitoring.

Selected candidate will be responsible for auditing/reviewing model life cycle and measure the effectiveness, accuracy, and adequacy of the Models. In addition to it, selected candidate will be expected to perform complex data research and analysis to support internal audits by designing and executing on data and analytic regarding audit procedures including creating processes, reporting, and data analysis methodologies to identify trends in large data sets. In addition, the position focuses on providing thought leadership and technical expertise across multiple disciplines to internal audit stakeholders and is recognized internally as "the go-to person" for the most complex data & analytics assignments.

Roles & Responsibilities:

- Lead planning, execution and reporting of internal audits related to model risk management and data analysis for senior management and regulators. Prepares analytics to summarize audit results to inform decision making and evaluation of audit conclusions.

- Establishes and drives innovative analytical audit processes leveraging technology to maximize benefits from traditional audits and replace manually intensive control testing.

- Analyzes large complex data sets, identify anomalies/trends/risks, and provide usable business insights.

- Sources and uses data analysis tools to automate audit testing. Develops techniques that support our established continuous auditing methodology.

- Identify critical areas for continuous monitoring, both from a Concurrent Audit perspective, and develop the necessary reports for monitoring.

- Makes, or assists in making, oral or written presentations to management throughout each engagement, discusses deficiencies, recommends corrective actions, and suggests best practice improvements.

- Review and test the model governance, development, implementation, validation to evaluate efficacy of generic scoring models built by the firm using statistical, ML and mathematical concepts.

- Identify and assess the model risks, controls, and issues and highlight gaps and recommendations for improvement.

- Evaluate compliance with applicable company policies and procedures and regulatory standards and best practices.

Experience and Skills:

- 8 - 12 years of experience in financial services industry experience, ideally in model risk governance, model risk audit, risk management and data analytics

- A master's degree in accounting finance, Business, Data Analytics, Statistics, Mathematics, or related fields.

- Certification of CA, CISA, CPA or CIA (or actively working towards) or other similar certifications is an added advantage.

- Strong proficiency in tools and technologies like R, Python, Spark, SQL, Pyspark, Hive, Tableau, Alteryx, Microsoft Access, PowerPoint, Excel, and SharePoint.

- Familiar with data movement and file transfer methods and tools. Experience designing and evaluating data and analytical audit procedures to drive efficiency and insights to stakeholders.

- Ability to review models from multiple functional areas - Consumer, Commercial, Microfinance, Fraud and Matching algorithms.

- Experience in building/auditing with predictive modeling; exposure to risk scorecards will be an advantage.

- Demonstrated ability to understand complex technologies, business processes, regulations, and emerging risks.

- Self-starter with the ability to manage and prioritize responsibilities.

- Ability to work independently, handle ambiguous situations and exercise judgement in variety of situations.

- High degree of responsibility and ownership, strong multitasking, coordination and tenaciously looking for ways to get results.

- Team player with proven skills in influencing people without having direct management authority.

- Self-driven performer with established skills in tracking self and project performance, anticipating and recognizing problems and escalating issues appropriately.

- Strong ability to interact and communicate both written and verbally with people at all levels, both technical and non-technical, in a dynamic environment where interactions are not always in person.

- Strong risk analysis and problem-solving skills.

- Must be flexible to ensure assessments are performed timely and manage multiple assessments simultaneously.