New York, New York, United States
Senior data executive with 12+ years of data science and analytics experience, and 7+ years building and leading enterprise-wide data functions. Proven leader in delivering revenue and cost savings through predictive modeling, AI-driven automation, and modern cloud architecture. Passionate about scaling high-performing data teams, launching firmwide data strategies, and embedding analytics into commercial decision-making across private equity, investment banking, and asset management.
Built and scaled the firm's first enterprise-wide data function, transforming a legacy business reporting group into a centralized analytics, data science, and AI team supporting 350+ senior bankers across all business lines. Partnered with senior leaders and department heads to quantify firm-wide data requirements, execute on analytics/ML/AI projects, and promote a data-driven culture.
Founded and led the firm's data strategy and analytics efforts, reporting to the CFO and executive team, and overseeing development and execution of all data projects. Established and communicated TS's data strategy roadmap, partnering with senior stakeholders across acquisitions, asset management, finance, and marketing. Championed a data-first internal culture prioritizing innovation, data literacy, and analytics-based insights.
Global Industrials Group Advised on mergers and acquisitions opportunities and investor relations with financial modeling and market analysis, supporting deal origination, valuation modeling, and advisory for industrials industry clients and financial sponsors. L3Harris: Conducted comprehensive M&A analysis of business overlaps and synergies, developed financial model and valuation projections, and created deal announcement investor materials to support the largest-ever defense industry merger of L3 Technologies with Harris Corporation ($33.5Bn, announced Oct 2018).
Portfolio Strategy Leveraged quantitative analytics frameworks including sensitivity analysis, Monte Carlo simulations, and historical backtesting to design bespoke investment portfolios and develop proprietary portfolio optimization tools for institutional investors.
Risk Management, Global Corporate Payments Developed ML models (propensity to win, magnitude of spend, default likelihood) using Python and SAS to identify and recommend high-value prospects. Achieved a 150% increase in campaign ROI and reduced firm risk exposure.