Designed for curious, future-focused problem-solvers, the program puts students right where the action is — in a world where numbers move markets, advanced analytics guide every decision, and AI is reshaping the global financial landscape.
Unlike traditional finance programs, the master’s in Financial Analytics emphasizes machine learning, predictive modeling, and big-data applications in investments, corporate finance, and risk management. Students also gain deep insight into financial theory and instruments, including derivatives, credit analytics, and regulatory modeling. The curriculum ensures that students understand both the “why” and the “how” behind modern financial decision-making.
Manhattan University’s Low-Residency Executive Education programs blend flexible online courses with limited, curated NYC residency weekends, offering working professionals an accelerated path to advanced degrees enriched by industry access, faculty engagement, and high-impact networking.
Students in the program will have access to Bloomberg terminals, Python, R, Tableau, SQL, and a proprietary financial database — the same platforms used by global banks, hedge funds, fintech firms, and regulators. The hybrid format also supports working professionals seeking to advance or pivot their careers without pausing their professional journeys.
“Financial services are being transformed by analytics, automation, and AI,” said Hany Guirguis, Ph.D., Dean of the O’Malley School of Business. “This program prepares students to thrive in that environment — not just by learning financial theory, but by applying advanced analytics to real-world markets.”
Graduates of the program are prepared to enter high-impact roles across Wall Street, fintech, banking, consulting, and regulatory agencies. Career pathways include quantitative analyst, financial data scientist, portfolio risk analyst, fintech strategist, valuation analyst, and regulatory analytics specialist — positions that increasingly rely on advanced modeling, AI tools, and real-time data interpretation. With deep training in financial theory, analytics, and industry-standard technology platforms, students graduate ready to evaluate markets, forecast risk, design data-driven investment strategies, and support critical financial decision-making. As financial services continue to shift toward automation and analytics-powered insight, demand for professionals with this specialized skill set remains strong worldwide.
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