Data Analyst


 About the Lab
The California Policy Lab translates research insights into government impact. Through hands-on partnerships with government agencies, CPL performs rigorous research across issue silos and builds the data infrastructure necessary to improve programs and policies that millions of Californians rely on every day. CPL's UCLA site is a dynamic and growing organization with nearly 20 full-time employees, half a dozen graduate student researchers, and numerous faculty affiliates.

CPL recognizes the value of having a diverse staff at all levels of the organization. We are looking for equity-minded applicants who represent and understand the diverse racial and ethnic, gender identity, sexual orientation, educational, socioeconomic, cultural, and disability backgrounds present in California. When you join our team, you can expect to be part of an inclusive and equity-focused community.

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The Role
The California Policy Lab is seeking a Data Analyst with a background or interest in labor economics, data science, and experience analyzing individual-level data. The Labor Specialist will contribute to our organization's proven track record of bridging the gap between academic researchers and government policymakers at the local level in Los Angeles, and at the state level in California. Among others, the role involves estimating equitable models designed to connect workforce services to those most in need. The California Policy Lab has compiled an unparalleled holding of administrative datasets with the goal of making actionable research a reality, and the Labor Specialist will have access to rarely available data to perform their project tasks.

The successful candidate will have exceptionally strong skills in data manipulation, as well as experience running, testing, and interpreting a variety of statistical models. In addition, we are looking for individuals with rigorous training in data science and experience building machine learning models. They will be passionate about using data to find innovative solutions to labor market problems facing California policymakers and workers. This position requires an individual who is able to work on research teams that run multiple projects concurrently. We seek highly organized individuals with superior written and verbal communications skills and excellent time management ability. The Labor Specialist will also be required to follow coding guidelines established by CPL and to contribute to the organization's efforts to build richly detailed documentation of the data we use.

Percentage of Time:
100

Shift Start:
9:00 am

Shift End:
5:00 pm

Qualifications for Position

15
Records

Qualifications

Required/Preferred

Substantive knowledge of quantitative research methods and causal inference

Required

Mastery of data analysis and data management in SQL, Stata, SAS, Python, or R

Required

Substantive knowledge of and interest in labor economics

Required

Attention to detail and ability to organize and document workflow

Required

Strong initiative and a resourceful approach to problem-solving

Required

Superior verbal and written communication skills

Required

Ability to work independently and as part of a team

Required

Ability to multi-task with demanding timeframes

Required

Ability to work discreetly with sensitive and confidential data

Required

Experience working in an academic or think-tank environment

Preferred

Substantive knowledge or experience in at least one of our five core research areas ? homelessness, criminal justice, poverty, education, or labor

Preferred

Project management experience

Preferred

Understanding of relational database concepts and experience with SQL

Required

Experience with business intelligence tools such as Tableau or PowerBI

Preferred

Bachelor's degree in public policy, economics, statistics, and at least one year of relevant research experience, or other relevant field or equivalent experience/training.

Required

Additional Posting Information

Bargaining Unit:
99-Policy Covered

Application Deadline:
07-31-2023

External Posting Date:

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