Data Analyst Save

About us: The Center for Violence Prevention Research conducts rigorous science by developing and evaluating and community-based strategies that expand the evidence base for what works to prevent violence against women and children. By answering the questions “Does it work?” and, “How, for whom, and in what settings?” the Center will improve existing prevention strategies, programs, and policies. You can learn more at scienceofviolence.org. We are quickly growing and need team members who are committed to our mission and can operate with flexibility in a developing organization. 

Position Summary

The Center is seeking a Data Analyst to conduct rigorous quantitative analyses that advance understanding and prevention of violence in its many forms. The analyst will work with complex data sources—including national surveillance datasets (e.g., NCANDS, NVDRS, NaSCEV), randomized control trial data, and observational data—and apply advanced methods such as longitudinal modeling and missing data imputation. This role requires comfort with restricted-access datasets, strong data management skills, and adherence to gold-standard practices in reproducibility, peer review, and research integrity. The ideal candidate combines methodological expertise with a commitment to producing actionable, high-quality research that informs policy and practice.

Specific duties include:

Data Analysis

• Conduct quantitative analyses on projects aligned with the Center’s mission.
• Clean, screen, and validate datasets while ensuring compliance with data security and protection requirements.
• Develop and implement analysis plans with clear timelines.
• Conduct preliminary descriptive analyses and present findings in user-friendly formats to team members, flagging noteworthy insights.
• Prepare main analyses, write data analysis and results sections of manuscripts, and maintain detailed documentation of analytic procedures.
• Conduct power analysis and preparatory analyses to support grant writing and study design
• Save and archive code for replication purposes.
• Establish and implement a peer review plan for analytic approaches and outputs to ensure accuracy and integrity.
• Adopt gold-standard data management practices, including version control, secure data storage, and comprehensive documentation.
• Maintain reproducibility standards by archiving clean datasets, code, and analytic decisions in accessible repositories.
• Conduct sensitivity checks, robustness tests, and model diagnostics to validate findings.

Specific analysis skills

Core Analytical & Statistical Skills

• Applied statistical modeling: Proficient in Generalized Linear Models (GLM), non-linear modeling, and hierarchical/multilevel modeling for complex data structures.
• Causal inference methods: Familiarity with quasi-experimental designs, including difference-in differences, propensity score matching, and instrumental variable techniques.
• Epidemiological analysis: Understanding of study designs such as cross-sectional, repeated measures, and longitudinal cohort analyses, with the ability to interpret results in public health contexts.

Data Management & Integration

• Data wrangling and integration: Skilled at merging large administrative and national surveillance datasets (e.g., birth, death, hospital, or crime records).
• Data cleaning and quality control: Able to manage missing data, ensure data integrity, and prepare datasets for reproducible analysis.
• Data documentation: Maintains clear, well-documented codebooks and analysis pipelines to ensure transparency and reproducibility.
• Statistical software proficiency: Expert in R or Python (preferably both), with experience using libraries such as:

o R: tidyverse, lme4, glmnet, survey, ggplot2

o Python: pandas, statsmodels, scikit-learn, matplotlib/seaborn

• Database and web data (preferred but not required): Experience handling backend or web-generated data, using SQL and API-based data collection.
• Version control: Comfortable using Git/GitHub or equivalent for collaborative analysis.

Dissemination

• Write data analysis and results sections of scholarly articles for peer-reviewed publication.
• Present findings at local, state, and national conferences.
• Prepare analysis aspects of technical and non-technical reports, briefs, and research summaries.
• Support internal teams in translating research findings into practice and policy applications.

This job description is not exhaustive and may evolve with organizational needs. Duties, responsibilities, and activities may change at any time with or without notice.

Required Qualifications

• PhD in statistics, epidemiology, public health, social work, psychology, public policy/administration,

or related field OR Master’s degree and at least 2 years of experience.

• Proficiency in data management and statistical analysis, preferably using R.
• Experience with advanced analytic methods (e.g., difference-in-difference analysis).
• Authorization to work in the United States.

Ideal candidates will have:

• Familiarity with public health approaches to violence prevention
• Strong methodological, writing, and communication skills.
• Experience working independently and collaboratively in mission-driven environments.
• History of scholarly productivity, with motivation to lead projects toward peer-reviewed publication.
• Ability to translate scientific findings for non-scientific audiences.
• Expertise in rigorous quantitative analysis and violence prevention research.

What you can expect from The Center

• $80,000-$94,000/year depending on education, years of experience, and contribution to the field.
• Work from home stipends for phone, internet, utilities, and equipment. Staff must maintain a home office with internet and phone access; a computer and necessary software will be provided.
• Health insurance plan.
• The Center staff work from home. However, we are a highly collaborative, active team with regular interaction.
• The Center is an equal opportunity employer. All applicants will be considered for employment without regard to age, race, ethnicity, religion, sex, sexual orientation, gender identity or expression, veteran or disability status. We are committed to fostering a supportive environment for our employees.

Organizational Values

The Center is committed to advancing rigorous, objective, and accessible science. We recognize that the most impactful science is that which can inform decision-making across communities, regardless of race, ethnicity, gender identity, religion, socioeconomic status, political affiliation, or other perspectives. Staff are expected to present themselves and their work in a manner that reflects neutrality, integrity, and inclusivity when operating on behalf of the Center.

Application Instructions

Interested candidates should submit:

• Cover letter
• Curriculum Vitae (CV)
• Writing sample relevant to the job posting