Lead - Model Risk Auditor - Data Analytics (8-12 yrs)

Lead - Model Risk Auditor - Data Analytics

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 TUCIBIL 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.

- Communicate the audit findings and recommendations to senior management and stakeholders.

- Follow up and verify the resolution of audit issues and actions.

- Performs other related duties as assigned.

- Build collaborative working relationships with internal stakeholders (appropriate levels of management)

- Confidently lead meetings to discuss audit issues with management, ensuring their understanding of associated risks, root causes, and the actions needed to remediate.

- Maintain and update the knowledge of relevant regulations, standards, and best practices for model risk management.

- Operate autonomously and manage tasks at hand independently.

- Take ownership of the assigned tasks and interact with other IAA members in working towards departmental goals.

- Monitors ongoing remediation of deficient systems or processes and develops updates or modifications to recommendations and findings as needed.

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.