Who We Are

Casandra Hockenberry

Program Manager

The Council of State Governments Center of Innovation

Casandra manages the Apprenticeship Data Alignment and Performance Technical Assistance Center, the Overseas Voting Initiative, and other research areas related to cybersecurity, data and privacy. As a part of her work at CSG, Casandra regularly convenes state policy makers to facilitate the exchange of innovative policies and practices. Her work focuses on improving the quality of data collection in the states to help states inform policy decisions.

Chip O'Connell

Research Data Scientist

The Council of State Governments Center of Innovation

Chip O’Connell is a Research Data Scientist at The Council of State Governments Center of Innovation. He earned bachelor’s degrees in Political Science and Economics from Marshall University and expects to earn his PhD in Political Science from the University of Kentucky in 2022. Prior to coming to The Council of State Governments, Chip instructed Political Science classes in topics such as political analysis. He loves playing with data and enjoys every step of the data analysis process.

The Turnout

Jared Marcotte

The Turnout

Jared Marcotte’s expertise lies in the areas of technology and policy, cybersecurity, and data standardization. Jared has served as Senior Technology Advisor to The Council of State Governments Overseas Voting Initiative, a collaborative effort between CSG and the U.S. Federal Voting Assistance Program, as part of his work at The Turnout. In this capacity he assisted state and local officials in the development of the ESB Data Standard and works with state and local officials toward data alignment. Along with other members of The Turnout, he works with state officials and federal agencies to assess data governance and create product certification programs. He was Senior Engineer at New Organizing Institute, Web Developer/Designer at Six Apart, and Software Engineer at IBM. He has also served as Elections Technology Officer and Manager of the Voting Information Project at The Pew Charitable Trusts.

John Dziurlaj

The Turnout

John Dziurłaj’s involvement in the technology and process modeling space spans over a decade. John has worked in a large urban county as well as the state, the latter of which he was responsible for the maintenance of the statewide voter registration database. He has worked on data driven projects including database design, development, and migration. He has broad experience in data architecture designing ETL processes, building data structures, and semantic modeling. He has been a constant advocate for open data standards, serving on committees as well as incorporating them into this work. Since 2016, he serves as the chair of the NIST-EAC Working Group on Election Modeling, which works to build a common understanding of elections across the country

Brian Guayante

The Turnout

Brian Guayante is a programmer with more than five years of experience in tech. Formerly specializing in hardware, network infrastructure, and support, he has worked for the University of California, the XPRIZE Foundation, and human-I-T, a non-profit organization that processes e-waste into donatable electronic devices for families in the Los Angeles area. More recently, Brian worked with the County of Los Angeles to provide support for in-person voting sites during the 2020 General Election. Brian is a graduate of the University of California, Riverside, and General Assembly, where he learned and built web applications using the MERN (Mongo, Express, React, and Node) stack.

Mathematica

Sheldon Bond

Mathematica
 
A technically trained program analyst in the Data Analytics Division, Sheldon Bond (A.M., Government, Harvard University) serves as team leader for Requirements, IV&V, and Data Validation tasks for the SCSEP project. He has worked on SCSEP since 2010 and has played a leading role in all aspects of the integration, system, and regression testing. He develops requirements for system enhancements, writes technical specifications, and performs data analysis. In addition to his work on SCSEP, he has performed integration testing and data analysis for a variety of programs, including TANF, UI, PREP and the Elderly Nutrition Support Program (ENSP). He knows a number of scripting languages, including JavaScript, Python and VBScript and I have extensive experience with statistical programming packages such as R and SAS.

Jonathan Ladinsky

Mathematica
Jonathan Ladinsky (Ph.D., Political Science, Massachusetts Institute of Technology) is a Senior Researcher of Program Improvement. He earned a PhD in political science from MIT where his dissertation addressed why and when wars start when empires and multi-ethnic states disintegrate. Since coming to Mathematica, his work focuses on the development of performance management systems, which includes the development of performance measures, data quality procedures, software development, and quantitative and qualitative data analysis, to support data-driven decision-making. Dr. Ladinsky has led projects for federal and state clients in the areas of education, health, labor, and welfare. Dr. Ladinsky’s research focus on the on the implementation of the Workforce Innovation and Opportunity Act’s performance management system for Department of Labor programs as well as the Department of Education’s Vocational Rehabilitation and Adult Education and Literacy programs.

Samina Sattar

Mathematica
 
Samina Sattar (M.P.A., Policy Analysis, NYU’s Robert F. Wagner School of Public Service) joined Mathematica in 2007. Her work at Mathematica has included evaluations in the Labor, Family Support, Education, and Early Childhood areas. Ms. Sattar is a seasoned qualitative researcher of workforce programs and systems and brings over 13 years of experience studying social programs to improve federal, state, and local policymaking. Her work has explored the personal and structural barriers to employment for job seekers—including youth, public assistance recipients, and justice-involved individuals. Ms. Sattar leads a team at Mathematica that is working on a portfolio of USDOL-sponsored studies of the apprenticeship system, including impact and implementation evaluations of grants to expand apprenticeship and an assessment of state capacity for apprenticeship expansion. She received her B.A. in Economics from Wellesley College.

Jonah Deutsch

Mathematica
 
Jonah Deutsch (Ph.D. Public Policy, University of Chicago) specializes in evaluation design, quantitative methods to evaluate the impacts of labor and education programs, and behavioral interventions. He has designed and executed studies of workforce development programs, social security programs, unemployment insurance, and teacher preparation programs. Dr. Deutsch leads the impact study for a nation-wide evaluation of DOL-funded apprenticeship programs. He is an expert in using administrative data systems within the workforce and education systems to study program effectiveness. Dr. Deutsch has also developed behavioral interventions, and evaluations of those interventions, for four DOL programs.

Grace Roemer

Mathematica
 
Since joining Mathematica in 1995, Grace Roemer (M.S., Urban Planning, Columbia University) has worked on a wide range of health and human services projects, leading primary (qualitative and quantitative) and secondary data collection efforts as well as development of federal performance management systems. She also has extensive experience providing training and technical assistance to state and grantee-run health and human services programs. Ms. Roemer currently leads the BUILD project; the BUILD team provides performance measures, data collection and data capacity, and continuous quality improvement support to 111 healthy marriage and responsible fatherhood (HMRF) grantees that are funded by ACF. The team maintains and enhances the comprehensive performance measures system (nFORM 2.0) used by all grantees, analyzes grantees’ performance data, and produces a range of products to support ACF’s learning agenda. She recently led the WIOA Implementation Evaluation and Strengthening Working Families Initiative Technical Assistance projects for DOL.

Robbi Ruben-Urm

Mathematica
 
Robbi Ruben-Urm (M.A., Communication and Information Studies, Rutgers University) began working at Mathematica in 1994 and has over 25 years of experience in project management, technical documentation, data collection, and operations management. She has collected and organized data to document programs and systems from agencies and states as well as developed training materials, systems documentation, analytical documents, and presentations. This included the review of business requirements documentation and mapping the business process flow of state Unemployment Insurance systems. Ms. Ruben-Urm has also served as project manager for more than 20 projects. Her project and operations management responsibilities have included client reports, monitoring staffing and budgets, drafting subcontractor agreements, assisting with webinar planning and overseeing help desks. She is currently coordinating the state data quality report operations for the T-MSIS Data Quality Tool project as part of the MACBIS project with CMS.

Katherine Campbell

Mathematica
 
Katherine Campbell (B.A., Economics, Hobart and William Smith Colleges) is a Data Analytics Developer whose work spans across DOL technical assistance, administrative data collection, , and R and Stata data cleaning and analysis work. She has experience drafting technical specifications, performing regression and quality assurance testing, and developing SQL queries for reporting purposes on the SCSEP project. She also leads data validation tasks and the Participant Individual Record Layout (PIRL) documentation task that maps fields in the new data collection system to existing PIRL elements. She is experienced in data cleaning and diagnostics for large scale education and labor projects.