Christopher Teixeira is a Principal Data Scientist in the Model-Based Analytics Department within the MITRE Labs. He’s responsible for providing his expertise in statistics, applied probability, modeling and simulation, and operations research to a variety of challenges that the federal government faces. In particular, he works directly with multiple federal agencies to identify potential solutions to the challenges they face and how best to use data to drive decisions they need to make. This includes helping them distinguish between the advantages and differences of varying analytical techniques. This breadth of knowledge and applications has led Chris towards becoming an expert at shaping efforts with sponsors including writing the contract language, cost proposals, and technical proposals across multiple efforts over the years.
Chris served in a variety of roles over the course of his career at MITRE. He first joined as an individual contributor serving several sponsors by applying his background in Applied Statistics and Operations Research. This includes supporting multiple federally funded research and development centers across a variety of projects, such as supporting the Department of Energy in understanding how to safely and effectively treat nuclear waste and helping the Veterans Benefits Administration use sophisticated modeling techniques to better serve veterans. Recently, Christopher led a project that used a variety of advanced analytical techniques to define and identify opioid prescribing behaviors. In this role, he led a team of 20 data scientists and presented this material in public meetings to a group of Chief Medical Officers, State Commissioners, public health experts, and data scientists. He earned an M.S. in operations research from George Mason University and a B.S. in mathematics from Worcester Polytechnic Institute.
MS in Operations Research, 2010
George Mason University
BSc in Mathematics, 2006
Worcester Polytechnic Institute
I support multiple clients by using various analytic techniques including but not limited to Optimization, Data Mining, Natural Language Processing, and Machine Learning. These skills are applied through a combination of R, Python, SAS, and Netezza.
I serve as one subject matter experts in the following areas: NLP and text analytics, optimization, and big data solutions. Typical duties include hosting “lunch and learns”, providing support on business development efforts, and produce code samples in multiple programming languages.
Worked with a team to determine the best use of IBM’s analytical skills to help Aetna improve their business. Modified a SAS multiplicative regression model to be more flexible with data and improve efficiency. Determine the important factors in improving care management efficiency for existing programs at Aetna.
Supported JIEDDO using various analytical techniques including Analytic Hierarchy Process and Regression Analysis. Created and tested a metric to help support decision making for various groups of people working with JIEDDO. Improved existing products in Excel and Access using SAS code. Created SAS Stored Processes to help streamline report generation. Improved raw data cleansing and formatting using regular expression parsing. Streamlined a process to parse XML files and create new databases from the results. Developed SAS stored processes to support business intelligence and analytics. Designed a database to enhance reporting and help determine an optimal solution to a resource allocation problem.
As an Operations Research Analyst, I had the responsibility for taking a list of directions and being able to produce a solution with little to no guidance. This involved working with EXCEL, VBA, SAS, ARENA, and AnyLogic.
I was responsible for the team of interns. I worked with other SAIC employees to both screen and interview applicants for the Operations Research internships. I provided a list of tasks, providing feedback on work, and supervised the team of interns.
This list of projects represents the details of my experience across my career and how I supported customers' decision making on complex challenges.