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Finance Planning & Analysis (“FP&A”) partners with firm and divisional leadership to understand and manage risks and create solutions through quantitative analysis, projecting and forecasting. We are responsible for firmwide business planning and transformation initiatives. The business planning function collaborates with groups across the firm to develop and manage the firm’s forward looking strategic and financial plans, including the firm’s P&L and financial resources.
Our team collaborates with each of the firm’s revenue divisions, Controllers, Corporate Treasury, and Risk, among other groups at the firm, to develop models which inform firmwide strategic planning. These models analyze sensitivities of financial projections, as well as actual performance relative to projections. Professionals in the FP&A division have an analytical mindset, exhibit intellectual curiosity and are from diverse academic backgrounds.
We are looking for an [associate or vice president] to join the FP&A Strats team in New York. FP&A Strats, like other “Strat” efforts at GS, has the mandate to drive insights and innovation in the FP&A division through the use of analytics. We may leverage a broad range of cross-disciplinary techniques including quantitative finance, data science, machine learning, and optimization.
The position involves solving real-world business problems in the financial and strategic planning process, working in tandem with other FP&A professionals and across divisions. The role requires a combination of the following competencies: a strong foundation in quantitative and data science techniques, an understanding of the financial markets and financial modeling, strong communication skills including to non-technical audiences, and software engineering.
Projects will be driven by business need but may include the following: developing simulations of firm / business performance based on macro variables; creating explanatory analysis of aggregate business performance relative to forecasts; enhancing and building predictive models of volumes/market share/fees; and developing optimizations of forecast PnL relative to resource consumption. We expect a successful candidate to be self-led, entrepreneurial, and capable of managing the delivery and adoption of key products.
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