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Director, Advanced Analytics and Risk Management
2 months ago
Fannie Mae is seeking a highly experienced and innovative leader to join our team as the VP, Internal Audit - Data Analytics & AI. This executive-level position is responsible for overseeing the development and implementation of our data analytics and AI strategy, fostering a culture of innovation and continuous improvement within the audit department.
Key Responsibilities- Provide executive leadership to implement our data analytics and AI strategy for internal audit and promote a culture of innovation and continuous improvement.
- Lead the advanced data analytics program and team to foster and grow data analytic usage in complex and multifaceted validation and audit testing.
- Promote the use of advanced analytics and automation methods and techniques across the audit department through delivery of proof-of-concept engagements, demonstrations, and education and information sessions.
- Lead the implementation of new data analytics, artificial intelligence, machine learning, RPAs, and other advanced technologies to improve audit quality and efficiency.
- Manage and oversee the advanced analytic work to ensure it is delivered accurately, timely, and complete, adhering to Internal Audit documentation standards.
- Design and implement Continuous Auditing techniques and methodology, enhancing processes to optimize the efficiency and effectiveness with which assurance work is executed.
- Manage and oversee the prioritized Audit Innovation Solutions to optimize the value to Internal Audit.
- Assist and provide guidance in evaluating the effectiveness of delivered audit innovation solutions to ensure the solutions remain fit-for-purpose, accurate, complete, and timely.
- Facilitate the communication of delivered audit innovation solutions to broader audit department, individual teams, and audit stakeholders, as necessary.
- Provide hands-on technical leadership by architecting, designing, and developing leading-edge audit innovative solutions across the technology stack focused on data innovation, workforce productivity, and new capabilities.
- Identify and assess the risks associated with new technologies and develop and implement controls to mitigate the risks accordingly to ensure reliability of the audit results.
- Bachelor's degree in Computer Science, Data Science, Machine Learning, Electrical & Computer Engineering, Information Science, Information Systems, Finance, Business, or related major.
- Master of Science background strongly preferred.
- Specialized audit certifications (e.g., CIA, CSFA, CISA) are helpful.
- 15 years of relevant experience, ideally in data science/analytics, programming, software engineering, control, audit, or risk roles and/or public accounting, with an emphasis in machine learning.
- Working experience in large financial institutions or Fintech companies with a detailed understanding of the application of advanced data analytics and AI technologies and thorough knowledge and understanding of current emerging technologies.
- Team management experience with a proven track record on driving change with a sense of urgency and delivering large transformational projects.
- Effective project management skills, make sound decisions, and exhibit initiative and intuitive thinking.
- Strong oral and written communication, presentation, and facilitation skills.
- Delivered high-quality assurance service through the deployment of Data Analytics and AI use cases and fostered effective collaboration between the central DA team and business audit teams.
- Drove innovation that delivers long-term value for a department through ideation, research, and collaboration with other functions and external partners.
- Developed human capital through establishing a minimum baseline of DA skills and built SME expertise through training and recruitment.
- Worked with internal audit teams and other company functions to onboard new infrastructure and tooling based on requirements.
- Strong ability to structure and scope complex problems.
- Articulated business objectives, business risk, processes, and controls to both technical and general audiences.
- Worked within Internal Audit or adjacent risk management space and knowledge of core Audit functions and responsibilities.
- Worked collaboratively in a matrix environment with direct reports, peers, and senior leadership teams.