Research Data Analyst 1 RP

RSCH DATA ANL 1 RP (005272)

UCPath Position ID: TBD_1000139

Position Description History/Status

Approved Date:

8/18/2026 3:44:50 PM

Date Last Edited:

8/18/2026 3:44:48 PM

Last Action Effective Date:

Organization Details

Business Unit (Location):

LACMP

Organization Code:

2400O

Organization:

UCLA FIELDING SCHOOL OF PUBLIC HEALTH  

Division Code:

2410D

Division:

PUBLIC HEALTH DIV                      

Department:

192000 - COMMUNITY HEALTH SCIENCES

Position Details

UCPath Position Number:

TBD_1000139

Position Description ID

262638

UC Payroll Title:

RSCH DATA ANL 1 RP (005272)

Personnel Program

Professional and Support Staff (PSS)

Salary Grade:

STEPS

Job Code FLSA:

Non-Exempt

Union Code (Collective Bargaining Unit):

RP: Research and Public Service PR

Employee Relations Code:

E: All Others - Not Confidential

Employee Class (Appt Type):

4 - Staff: Limited

Full-Time Equivalent (FTE)

0.5

SUPERVISION

UCPath Reports to Position Number:

40063919

Reports to Payroll Title:

Asst Prof

UCPath Department Head Position Number:

40063918

Department Head Payroll Title:

Dept Chair

SUPERVISION - Indicates that the incumbent performs a variety of routine duties within established policies and procedures or by referral to the supervisor’s guidelines.

POSITION SUMMARY

The Research Analyst will support research projects focused on dementia, cognitive aging, and social epidemiology under the supervision of Dr. Ruijia Chen. The primary responsibilities will involve working with large administrative healthcare databases, including Medicare claims data, to develop and validate dementia identification algorithms. This position is ideal for candidates with strong quantitative skills who are interested in aging, Alzheimer's disease and related dementias (ADRD), social determinants of health, or causal inference.

The UCLA Fielding School of Public Health aims to build health and equity, and to drive positive change for all people. We act on this mission through initiatives in three core areas: education, discovery, and service. In each of these realms, we affirm our commitment to developing leaders and evidence-based solutions, and to working in partnership with communities to promote health and well-being in ways that are innovative, respectful, and inclusive.

Administrative

1. Assist with the preparation, management and analysis of large Medicare claims datasets.

2. Develop, implement, and evaluate algorithms to identify dementia and Alzheimer's disease using Medicare claims data.

3. Compare and validate alternative dementia ascertainment algorithms using clinical and survey-based reference standards.

4. Conduct statistical analyses using longitudinal administrative and epidemiologic datasets.

5. Clean, merge, and manage large datasets from multiple sources while ensuring data quality and reproducibility.

6. Write well-documented and reproducible analysis code using R and/or SAS.

7. Perform literature reviews related to dementia identification, cognitive aging, and Medicare claim forms.

8. Prepare tables, figures, and summary reports for manuscripts, grant applications, conference presentations, and progress reports.

9. Participate in weekly research meetings and contribute to project planning and scientific discussions.

10. Collaborate with investigators and research staff across multiple institutions as needed.

11. Maintain organized documentation of data processing pipelines, analytic decisions, and research outputs.

100%

•

Performs other duties as assigned.

•

Complies with all policies and standards.

•

Complies with the University of California, Los Angeles (UCLA) Principles of Community.

•

This position description is not intended to be a complete list of all responsibilities, duties or skills required for the job and is subject to review and change at any time, with or without notice, in accordance with the needs of the organization.

QUALIFICATIONS

Master's Degree

in public health, data science, computer science, economics, public health, or a related quantitative field.

Preferred

Strong programming experience in R.

Required

Experience working with large administrative or healthcare datasets.

Required

Excellent data management and statistical programming skills.

Required

Strong organizational skills and attention to detail.

Required

Ability to work independently while managing multiple projects and deadlines.

Required

Excellent written and verbal communication skills

Required

Experience working with Medicare claims, CMS data, or electronic health records.

Preferred

Familiarity with dementia or Alzheimer's disease research.

Preferred

Experience developing disease identification algorithms or prediction models.

Preferred

Knowledge of longitudinal data analysis, survival analysis, machine learning, or causal inference methods.

Preferred

Experience using Git or other version control systems.

Preferred

Previous experience contributing to peer-reviewed publications.

Preferred

SPECIAL REQUIREMENTS AND/OR CONDITIONS OF EMPLOYMENT

Background Check: Continued employment is contingent upon the completion of a satisfactory background investigation.

LOCATION AND PHYSICAL, ENVIRONMENTAL, MENTAL (PEM) REQUIREMENTS

Environment and Work Location Information

Environment Type:

Non-Clinical Setting

Location Setting:

Campus

Location:

UCLA

Standing/Walking

X

Sitting

X

X

Bending/Stooping

X

Squatting/Kneeling

X

Climbing

X

Lifting/Carrying/Push/Pull 0-25 lbs

X

X

Lifting/Carrying/Push/Pull 26-50 lbs

X

Lifting/Carrying/Push/Pull over 50 lbs

X

Physical requirements other

X

Chemicals, dust, gases, or fumes

X

Loud noise levels

X

Marked changes in humidity or temperature

X

Microwave/Radiation

X

Operating motor vehicles and/or equipment

X

Exposures other

X

Sustained attention and concentration

X

X

Complex problem solving/reasoning

X

X

Ability to organize & prioritize

X

X

Communication skills

X

X

Numerical skills

X

X

Mental demands other

X

X

Classification 3:  Position in which exposure to blood, body fluids or tissues is not part of the position description. The normal routine task involves no exposure to blood, body fluids or tissues and the employee can decline to perform tasks which involve a perceived risk without retribution.