Firmwide Modeling & Analysis (FM&A) is a global team within the Office of the Chief Financial Officer, responsible for design, development and deployment of various macroeconomic and econometric models, and broader Data Science efforts, including Artificial Intelligence and Machine Learning (AI/ ML) in the Firmwide P&A (Planning & Analysis) organization. As the Head of Firmwide Modeling & Analysis you will play an integral leadership role in setting and communicating strategic vision, steering t... more details
Firmwide Modeling & Analysis (FM&A) is a global team within the Office of the Chief Financial Officer, responsible for design, development and deployment of various macroeconomic and econometric models, and broader Data Science efforts, including Artificial Intelligence and Machine Learning (AI/ML) in the Firmwide P&A (Planning & Analysis) organization.
As the Head of Firmwide Modeling & Analysis you will play an integral leadership role in setting and communicating strategic vision, steering the Modeling and Analytical efforts and furthering the Data Science agenda in the Firmwide P&A organization. This role will call for extensive collaboration with partners across Risk, Finance, Technology, Chief Data & Analytics Office (CDAO) and the firm’s broader Data Science community. Strong analytical skills complemented by outstanding written and verbal communication skills are a must for this role. The role will also have exposure to senior leaders and provide the opportunity to develop important leadership and analytical skills required to advance in the Firm.
Job responsibilities
Lead the design, development and execution of various Data Science and related modeling and analytical efforts within the Firmwide P&A organization, working closely with key partners across Risk, Finance, Technology, Chief Data & Analytics Office (CDAO) and the firm’s broader Data Science community.
Play a leadership role in setting strategic vision and furthering the Data Science agenda, including leveraging AI/ML to create value within an organizational context.
Lead communications and meetings across diverse functions, locations and businesses to facilitate discussions, drive priorities and consensus amongst stakeholders and senior management.
Develop executive-level presentations and explain key analytical elements in a manner that is appropriately tailored to a diverse target audience.
Lead ad-hoc analyses and conduct Econometric and Data Science research as needed.
Stay abreast of current trends in economics, financial markets and analytical innovations, and anticipate implications for modeling and financial forecasting.
Required qualifications, capabilities, and skills
Strong quantitative skills: Advanced Graduate Degree (Master’s or PhD) in a Quantitative Field: Mathematics, Statistics, Quantitative Finance, or related field.
10+ years of work experience in quantitative modeling (stochastic, econometric)/ research / forecasting / data analysis for a leading financial institution is required.
Excellent communication (verbal and written) skills, with the ability to prepare and present executive level presentations.
Ability to view problems through a “big picture” lens, take concepts from ideation to execution and provide strategic guidance and oversight to a quantitative team.
Strong programming skills (e.g., Python, R) and advanced Excel and Microsoft Office skills are required.
Strong culture carrier and inclusive leader who leads by example. Inquisitive nature, ability to ask the right questions and escalate issues.
Organized, proactive, self-starter with high attention to detail, able to work in a fast-paced, results-driven environment with a proven track record of strong multi-tasking abilities in executing against deliverables and meeting deadlines under pressure.
Preferred qualifications, capabilities, and skills
Familiarity with economics, financial products and financial forecasting concepts is a plus.
Expertise in a broad array of AI techniques (e.g., ML, NLP, semantic searching, LLMs and RAG) is considered a plus.
Experience building and managing global analytical teams across multiple geographic locations is a plus.
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