Working on solving the hardest engineering problems using machine learning and artificial intelligence for U.S. Federal agencies.

Managing pre-sales data science activity for Federal civilian agencies, helping organizations unlock the potential of AI with the hardest use cases.

Managing a team of eight data scientists responsible for delivering customer enablement and success in machine learning. Focused on improving a HR solution in the Federal space to help transfer hiring across the government.

As a customer facing data scientist, I work with DataRobot's public and private sector clients to develop machine learning models at scale using the company's AI-native autoML platform. I help customers define their use cases for machine learning, provide training and hands-on support to customers modeling efforts, and assist in ensuring models are deployed to production and providing real-time prediction scoring for each business case.

As Gallup's principal data scientist, I provide strategy and advisory services to clients on data- and analytic-based projects, developing repeatable, scalable solutions. Internally, I manage the technical development of a team of eight data scientists and engineers, while guiding development of data science throughout Gallup by providing analytic thought leadership.

Provide technical oversight for a team of nine data scientists and engineers to meet client needs. Provide mentorship, strategy guidance, and technical expertise across a range of enterprise and government projects. PI or Co-PI on multiple government contracts.

Worked as a data scientist on enterprise and government clients, helping to build predictive models and forecasts for customers, using Gallup polling data and other resources to best meet clients' needs.

Taught a newly-designed course on data science in business for second-year MBA students. The course stressed basic data science skills as well as how to make sense and relate technical results to non-technical audiences to enhance business decision-making. A second, modified course was developed and taught at Georgetown for upper-year undergraduate business students in spring 2019. Both courses stressed experiential learning and group work to develop and instill core concepts of data science.

Picwell provides people with greater information and clarity while making health insurance decisions when purchasing on open exchanges. This helps ensure people make the right health insurance choice for themselves and their families.As a data scientist on the production analytics team, I sat at the intersection of research and production. Working with other data scientists and software engineers, I helped ensure our production pipeline reflects the best in analytics to ensure a great experience for clients.

As a fellow, I rounded out my skill set for continued work in data science. As part of the program, I built a better prediction model for food delivery wait time with a food delivery service in Nairobi, Kenya. This work utilized predictive modeling, spatial analysis, and extensive data wrangling.

I managed quantitative analyses using primary and secondary data to answer a variety of applied questions across the organization. Projects included credit score modeling, credit repayment analyses, route optimization, building quality assurance programs, and trial analysis. Analytic skills utilized included linear/non-linear regression (including use of propensity score matching), machine learning, A/B testing, Bayesian analysis, GIS analysis, and R/Python programming. In addition, I served as a technical consultant on research and evaluation design, calculating sample sizes, editing surveys, and creating analysis plans. I managed projects and staff development in analytic areas (R, Stata) across the organization.

I worked on a portfolio of applied international and domestic HIV research projects, focusing on the use of social network analysis. I worked on both complete and egocentric networks, employing dyadic (multi-level model) analysis as well as exponential random graph models and stochastic actor-oriented models. In addition, I executed a variety of data visualizations. Projects included understanding how social networks affect adherence to HIV medications in Uganda; HIV risk behaviors for men who have sex with men, commerical sex workers, and transgendered people in Lebanon; and the role a person’s social network has in perpetuating/stopping HIV conspiracy beliefs in Los Angeles. The overarching purpose of each HIV-related project was to understand how best to design and implement programs to reduce the burden of HIV in the focus population. In addition, I worked on education- and defense-related project evaluations using propensity score matching/weighting, times series analysis, and other econometric techniques. Fieldwork included Afghanistan, Uganda, and Iraq.

I provided on-site project management, primarily of randomized control trial evaluations. Typical activities included survey design, hiring/training/managing surveyors, overseeing data entry/management, monitoring project implementation, and conducting analyses. Clients included The World Bank, International Organization for Migration, United Nations Population Fund, Save the Children, International Rescue Committee, Columbia University, Single Stop USA, and Anytime Anywhere Learning Foundation. Fieldwork included Russia, Sierra Leone, Indonesia, Afghanistan, and Pakistan.

I participated in a year-long U.S. State Department-funded exchange program with Russia. I took courses in international relations at a Russian university while teaching a course on project design, management, and evaluation to undergraduate students. In addition, I co-founded a camp to increase youth tolerance among nationalities in the south of Russia.

I served as a Peace Corps volunteer in Kazakhstan, teaching accounting and business management classes to undergraduate students. Additionally, I consulted with small business entrepreneurs on start-up ventures and helped prepare grants for a local business incubator.