BNY is looking to leverage AI and advanced analytics within its Internal Audit department to enhance efficiency, effectiveness, and innovation in audit activities.
Requirements
- 5-7 years’ experience working in Quantitative, Statistical, Data Analytics, Data Science or AI/ML field
- Strong foundational knowledge of classical Data Science and Machine Learning models, grounded in first principles thinking to ensure rigor in model development
- Understanding of prompt engineering, retrieval-augmented generation (RAG), and integrating LLMs into real-world workflows.
- Hands-on experience with supervised and unsupervised ML techniques, including regression, classification, clustering, decision trees, ensemble methods, etc.
- Knowledge of deep learning and deep learning frameworks
- Experience with core ML libraries like scikit-learn, XGBoost etc.
- Strong Python skills in developing Gen/ Agentic AI and Data Science & Machine Learning solutions
Responsibilities
- Work with Internal Audit teams and fellow Data Scientists / Analysts to design self-service data products that enable auditors to more efficiently and effectively carry out all phases of audit lifecycle
- Support innovation and design of advanced AI and analytical tools for the audit department that extend beyond the scope of duties of Internal Audit
- Conceive and conceptualize Data Science, Machine Learning and Gen/ Agentic AI solutions to embed rigor and innovation in internal audit activities
- Collaborate closely with business teams and internal audit stakeholders to identify opportunities for implementing AI agents / digital employees across diverse business areas
Other
- Excellent communication and stakeholder engagement skills
- Self-Initiator and Thought Leader, who proactively identifies opportunities to apply AI/ML and analytics across audit and business functions; takes ownership of ideas from conception to delivery.
