Booz Allen Hamilton

Booz Allen Hamilton, a Fortune 500 company, has been at the forefront of strategy and technology consulting for more than 100 years. Today, Booz Allen is a leading provider of management consulting, technology, and engineering services to the US government in defense, intelligence, and civil markets, and to major corporations and not-for-profit organizations. The firm is a well-known, trusted, and long-term partner to our clients, who seek our expertise and objective advice to address their most important and complex problems. Booz Allen helps clients achieve success today and address future needs by applying our expertise in such areas as systems development, cybersecurity, advanced engineering, and innovation to design, develop, and implement solutions. We attribute the strength of our client relationships, the commitment of our people, and our strong financial position to our management consulting heritage, which drives our relentless focus on delivering value and enduring results to our clients. Our collaborative culture, supported by our operating model, helps our professionals identify and respond to emerging trends across the markets we serve. Our single profit and loss structure removes internal barriers and gives us the agility to adapt to changes in the market and ensures our focus on client missions and results. Over the past decade, Booz Allen’s high standing as a business and an employer has been recognized by dozens of organizations, including Fortune, Working Mother, Forbes, and G.I. Jobs.

Yes, you really can use this! - Applying Data Science to Real-World Problems

Thursday, March 2, 2017 - 5:00pm to 6:00pm
Schapiro Hall (CEPSR) Davis Auditorium
530 W 120th St.
New York, NY 10027
United States

Columbia Data Science Innovation Seminars

Ben Arancibia, Lead Data Scientist | Booz Allen Hamilton
Dan Liebermann, Lead Associate | Booz Allen Hamilton

Booz Allen Hamilton’s Dan Liebermann and Ben Arancibia will cover what it takes to get data science done in the real world. They will be sharing stories from the trenches – covering experiences and lessons learned from turning data science theory into reality when the problem (and the solution) are far from known. The talk will heavily engage the audience to hear their perspective, and cover the approach Booz Allen took to solve its clients’ problems. The goal is to get the audience thinking about what they would do in these situations and how they would apply their classroom experience.

The Cognitive Modeling Paradigm: An Experiment in Casual Inference

Monday, October 26, 2015 - 6:00pm to 7:00pm
Davis Auditorium, Room 412, Shapiro SEPSR
Columbia University
New York, NY 10027
United States

Alex Cosmas
Chief Scientist | Booz Allen Hamilton

The analytics community has invested significant resources in developing effective predictive analytical methods. However, even the most accurate predictive forecasts have limited value unless they can also provide clear action steps to bring about desired results.  In other words, the cause of the data is more important than the data itself.  Alex will introduce causal inference in the context of Bayesian Belief Networks (BBNs).  BBN’s produce accurate predictive forecasts, but with appropriate modeler input are also able to identify causal relationships between variables and pinpoint drivers of desired targets. With causal relationships identified, BBNs may be used in a prescriptive fashion in order to make actionable decisions.  Alex will dive into a case study in the aviation space which identifies causal drivers of daily flight operations on flight delays and allows us to prescribe delay-reduction plans by acting on controllable drivers.

Alex Cosmas

Alex Cosmas
Chief Scientist

Alex Cosmas is a Chief Scientist in Booz Allen Hamilton’s Strategic Innovation Group, specializing in predictive analytics across the transportation, travel, and consumer sectors. He is a recognized expert in the use of probabilistic and causal models to perform both deductive and inductive reasoning from large datasets. He has consulted for Fortune 100’s both domestically and internationally in the areas of demand modeling, consumer choice, network modeling, revenue management and pricing. He earned his Applied Physics from Columbia Engineering and M.S. degrees in Technology Policy and Aerospace Engineering, both from the Massachusetts Institute of Technology.

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