Christopher Teixeira

Christopher Teixeira

Co-Department Head

The MITRE Corporation


Christopher Teixeira, M.S. is the Co-Department Head for the Model-Based Analytics Department within MITRE. He is responsible for leading a department of about 50 individuals with backgrounds in policy, statistics, modeling and simulation, operations research, and data visualization expertise.

During his tenure at MITRE, he has supported 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. He earned an M.S. in operations research from George Mason University and a B.S. in mathematics from Worcester Polytechnic Institute.


  • Data Analytics
  • Applied Statistics
  • Operations Research


  • MS in Operations Research, 2010

    George Mason University

  • BSc in Mathematics, 2006

    Worcester Polytechnic Institute






Operations Research
















Principal Data Scientist

The MITRE Corporation

Jul 2014 – Present Massachusetts
Serves in many roles from individual contributor to technical lead and integrator. Exhibits expertise in a multitude of areas including technical solutions, communication skills, creativity, and vision to deliver a diverse set of technical solutions across different FFRDCs.

Senior Analytic Consultant


Aug 2012 – Jun 2014 Massachusetts

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.


Advanced Analytics Senior Consultant


Nov 2011 – Jul 2012 Virginia

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.


Operations Research Analyst


Jun 2006 – Oct 2011 Virginia

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.



State Engagement to Address Opioid Overprescribing and Misuse

Using analytics to understand opioid prescribing behaviors

Predicting Pitch Types

Predict the next pitch based on pitcher/batter histories.

Predictive Analytics in Child Welfare

Using analytics to understand opioid prescribing behaviors

Department of Energy Cost and Schedule Tool

Built a tool to determine changes to cost and schedule

Veteran Benefits Administration Command and Control Model

Understand bottlenecks and other systemic issues to increase system efficiency.

Children at Risk Research

Using analytics to determine risk factors associated with child fatalities

Financial Metrics Visual Model

Using simple modeling techniques to understand impact to corporate finances

Strategic Workforce Model

Model workforce dynamics to understand different hiring strategies.

Real Time Predictive Modeling

Design and implement a model to perform real time predictions.

MLB Player Similarity

Using stats to determine how similar baseball players are to each other.

Sentiment Analysis for specific Brand/Products

Translating unstructured text to interpret feelings towards a brand.

Customer Attrition Analysis

Using machine learning to predict which accounts are likely to be closed

Healthcare Claims Fraud

Statistical approach to determining regional based fraud in healthcare claims.

Optimizing Team Assignments

Creating fair and equal softball teams

Port Operations Analysis for PNNL

Simulate port operations to optimize tradeoff between speed and security.

NASA - Probabilistic Campaign Manifest Analysis Tool

Optimizing allocation of resources to maximize mission success

Transit Risk and Assessment Methodology

Risk analysis combined with data to protect transit systems.

Statistical Analysis of Defensive Production in Major League Baseball

Using analytics to understand opioid prescribing behaviors