Data Analyst

The Data Analyst will be responsible for providing data analysis, data cleaning, data storage, and data access support to Yale Law School (YLS) faculty and student research projects. Work with a variety of data types and sources and be able to provide technical support for research activities, including planning, organizing, conducting, storing, and accessing quantitative analyses and data.

Database Management

• Translate, update, and maintain our accumulated and growing datasets, devise displays and graphics, and generally improve their accessibility

• Request and integrate updated data into existing data sets

• Plan and program new databases, comprised of court data, case information, and original research, which are accessible to teams both within and outside of YLS
• Develop public-facing dashboards with functionality for the public to search and sort the data, display descriptive values based on search and filter parameters, generate data visualizations, etc.
• Develop API calls and other programming functions to automate the collection and management of frequently-used research data sources

Data Support

• Provide technical data processing, cleaning, and analysis assistance to YLS research projects, including generating reproducible data-cleaning code in accordance with individual project needs, providing information and updates on dataset contents and status, preparing datasets for statistical analysis, and providing preliminary descriptive summaries and statistics of data sets.

• Gather requirements from YLS faculty, staff, and students to provide support for empirical research projects, linking with other datasets, and identifying and seeking additional data that could supplement current projects.

• Utilize familiarity with external data sources-demographic, political, economic, business, and/or judicial-to integrate those data sources into YLS projects and communicate limitations in using those data.
• Translate data into impactful, meaningful visualizations for different audiences, including lawmakers, stakeholders, researchers, and laypeople., 1. Creates a relational database from existing study data currently stored in multiple data sources. Designs comprehensive and relational databases with advance knowledge of relevant applications impacting on the data analyses and reporting.

1. Develops and documents operational procedures for the collection, editing, verification and management of study data. Documents all study data files, data structure and relationships, variable definitions and data codes. Writes detailed specifications for analysis files and performs consistency checks.

2. Develops and implements relevant statistical programs to incorporate data from multiple studies/projects.

3. Organizes and creates documents and tables related to datasets; communicates with data sources about data accuracy and data dictionary.

4. Evaluates and analyzes data using accepted statistical techniques and statistical analysis software. Performs descriptive and multivariate statistical analyses of data, using computer software.

5. Uses advanced statistical knowledge to provide support in managing and analyzing data.

6. Designs and implements quality control measures to ensure accurate collection and processing of data. Ensures the integrity of databases used in analyses through development of essential data cleaning and checks, and data back-ups.

7. Responsible for the documentation and transmission of study data. Ensures that data are collected and completed in a timely manner at each site location.

8. May perform other duties as assigned.

1. Familiarity with data cleaning, storage, visualization, and analysis strategies, preferably R and relevant R packages, such as ggplot2, tidyverse, RShiny, etc. Proficiency in R, or able to translate preferred programming language / program to R.

2. Ability to create, curate, update, and maintain public-facing and internal databases Written and presentation skills communicating data and statistical concepts to an audience comprised of people with varying data-and statistical fluency

3. Familiarity with social science and/or legal research methods and analyses 4. Ability to work both collaboratively and independently on data cleaning and basic analysis

4. Skill with highly organized data storage and documentation techniques that promote transparent documentation, collaboration, access, and reproducibility

Preferred Skills and Abilities Experience beyond a bachelor’s degree coursework in working with data in R or equivalent program/ language is preferred. This preferred criterion may be met by: work on certification or certificate courses (e.g., Coursera, Data Camp, etc.), hands-on bachelor’s degree projects (e.g., relevant research assistantships, independent studies, or a senior thesis), completion of some coursework in a post-bachelor graduate program in statistics, data science, quantitative social science, or equivalent field.

Completion of a program is preferred but not necessary to fulfill the requirement. This experience should demonstrate successful work with preparing datasets, accessing research-oriented databases, generating data visualizations, and descriptive and inferential statistics., Master’s degree in statistics, computer science, business administration or a related field and two years of experience in data management and analysis or equivalent combination of education and experience. Experience with data collection and in coordinating efforts of multiple groups.