MC2 Research & Evaluation Analyst

Okpsych; Albuquerque, Northern (NM, KY); Hybrid; USD 80,000 - 90,000; Full time

Job summary

MC² Education seeks a Research & Evaluation Analyst to contribute to quantitative analyses, study design, and project coordination across applied research projects. The role involves flexible, remote work with around 30–35 hours per week and an emphasis on rigorous statistical programming and analytic outputs.

The candidate will perform data cleaning, descriptive and multivariate analyses, and prepare reproducible code and client-ready deliverables, while collaborating with senior researchers on

Qualifications

• Master's degree in a quantitative social science field.
• At least 2 years of professional quantitative research or evaluation experience.
• Experience with R or Stata and reproducible code.
• Experience with survey analyses from raw data to final tables/figures.

Responsibilities

• Clean, manage, and analyze quantitative data using R or Stata.
• Perform descriptive, inferential, and multivariate analyses for various study designs.
• Independently analyze survey data and prepare tables, figures, and outputs.
• Collaborate with senior researchers on study design and interpretation.
• Contribute to quality assurance, data collection, literature reviews, and reports.

Skills

Quantitative analysis

Descriptive statistics

Multivariate analysis

Statistical programming

Communication skills

Education

Master's degree in Statistics, Economics, Education, Public Policy, Psychology, Sociology, Biostatistics

Tools

R

Stata

Git

Quarto

R Markdown

Job description

Position Summary

Hourly Rate: Approximately $50/hour (1099 Consultant)

Hours: Flexible, estimated at 30-35 hours per week on average

Remote Position

MC² Education is seeking a versatile Research & Evaluation Analyst who can make strong quantitative contributions and flex across the many kinds of work required to move applied research projects forward. The analyst will support rigorous studies including randomized controlled trials (RCTs), quasi-experimental designs (QEDs), implementation studies, and large-scale survey analyses—while also contributing to project coordination, qualitative research, instrument development, data collection, literature reviews, and client-ready deliverables. This position is well suited for an early-career researcher who brings strong statistical programming and analytic skills, enjoys variety, learns quickly, and is comfortable shifting between independent analysis and collaborative project work.

Primary Responsibilities

• Clean, manage, and analyze quantitative data using R or Stata, with careful attention to accuracy and reproducibility.
• Conduct descriptive, inferential, and multivariate statistical analyses, including analyses for RCTs, QEDs, and observational studies.
• Independently analyze survey data and prepare clear tables, figures, and statistical outputs.
• Collaborate with senior researchers on study design, analytic strategy, interpretation of findings, and more complex methodological decisions.
• Conduct data validation and quality assurance; prepare codebooks, analytic datasets, and well-documented programming scripts.
• Contribute to qualitative interviews, coding and synthesis, data collection, instrument development, and literature reviews as project needs arise.
• Support day-to-day project execution, which may include coordinating activities, tracking tasks and timelines, communicating with partners, and preparing meeting materials.
• Synthesize findings and contribute to technical reports, evaluation briefs, presentations, and other products for technical and non-technical audiences.
  Participate in internal quality assurance reviews and shift comfortably among projects, teams, and responsibilities while maintaining high-quality work.

What Success Looks Like

The successful candidate is both a capable quantitative analyst and a versatile project contributor. They independently complete routine analyses—including survey analysis, data cleaning, descriptive statistics, regression models, and preparation of tables and figures—and produce well-documented, reproducible code. With equal confidence, they can step into unfamiliar or evolving assignments, ask good questions, organize the work, collaborate closely with colleagues, and deliver thoughtful, polished contributions across the research process.

Minimum Qualifications

• Master's degree in Statistics, Economics, Education, Public Policy, Psychology, Sociology, Biostatistics, or another quantitative social science field.
• At least 2 years of professional experience conducting quantitative research, program evaluation, or closely related applied research.
• Demonstrated experience supporting randomized controlled trials (RCTs) and/or quasi-experimental designs (QEDs).
• Proficiency in R or Stata, including writing reproducible code for data cleaning, management, and statistical analysis.
• Experience independently conducting survey analyses from raw data through final tables and figures.
• Strong understanding of statistical methods commonly used in applied social science research.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience with education research or program evaluation.
• Familiarity with longitudinal data, multilevel modeling, propensity score methods, or causal inference techniques.
• Experience working with administrative education data.
• Knowledge of reproducible research practices (e.g., Git, Quarto, R Markdown, or similar tools).
• Experience with qualitative or mixed-methods research, project coordination, instrument development, data collection, or client-facing deliverables.