Statistical Analyst/Programmer

RSCH DATA ANL 3 (006257)

UCPath Position ID: TBD_940538

Position Description History/Status

Approved Date:

11/8/2025 1:34:34 PM

Date Last Edited:

11/8/2025 1:34:32 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:

193500 - EPIDEMIOLOGY

Position Details

UCPath Position Number:

TBD_940538

Position Description ID

246244

UC Payroll Title:

RSCH DATA ANL 3 (006257)

Personnel Program

Professional and Support Staff (PSS)

Salary Grade:

Grade 23

Job Code FLSA:

Exempt

Union Code (Collective Bargaining Unit):

99: Non-Represented (PPSM)

Employee Relations Code:

E: All Others - Not Confidential

Employee Class (Appt Type):

1 - Staff: Contract

Full-Time Equivalent (FTE)

0.01

SUPERVISION

UCPath Reports to Position Number:

40184957

Reports to Payroll Title:

ASST PROF-AY

UCPath Department Head Position Number:

40038895

Department Head Payroll Title:

DEPARTMENT CHAIR

GENERAL SUPERVISION - Indicates that the incumbent develops procedures for performance of variety of duties; or performs complex duties within established policy guidelines.

POSITION SUMMARY

The Seamans Lab in the Department of Epidemiology at the Fielding School of Public Health at the University of California, Los Angeles (UCLA) seeks a highly motivated, collaborative, and skilled Statistical Analyst/Programmer to join our research team to contribute to impactful pharmacoepidemiologic research shaping drug safety and public health. Our team leverages large administrative healthcare claims datasets to evaluate medication use, safety, effectiveness, and outcomes in real-world populations. Our mission is to generate evidence that informs drug safety, regulatory decisions, and healthcare policy by applying advanced causal inference methods to observational data.

The ideal candidate will have experience with large, complex data (e.g., administrative healthcare claims databases or electronic health records); data structures for longitudinal data analysis; computer algorithms; and statistics or biostatistics.

The Epidemiology department in the Fielding School of Public Health is a national leader in preparing a new generation of epidemiologists. Through specialized methodologies, epidemiologists identify, track, and analyze how diseases and other conditions are caused, transmitted, and prevented, as well as how they are distributed throughout the population. Such information plays a critical role in guiding policies and other evidence-based strategies to promote health and work toward health equity. The vital importance of epidemiologic research was highlighted by the COVID-19 pandemic, in which epidemiologists have helped to track outbreaks and provide guidance on how the virus spreads in community settings.

Biostatistics and

Data Management

1. Conduct statistical analyses of large administrative healthcare claims databases to investigate drug safety, effectiveness, adherence, and comparative outcomes.

2. Clean, process, and manage complex claims data, ensuring data quality and integrity.

3. Prepare analytic datasets for pharmacoepidemiologic study designs (e.g., cohort studies, case-control studies, self-controlled designs).

4. Utilize advanced statistical techniques suitable for observational data, including propensity score methods, survival analysis, and longitudinal data analysis.

5. Collaborate closely with epidemiologists, biostatisticians, and clinicians, and regulatory experts to design studies and interpret findings.

6. Prepare detailed analytic reports, data summaries, and visualization to communicate study results effectively.

7. Support scientific publications and grant proposals.

8. Ensure adherence to data privacy and security regulations (e.g., HIPAA) and maintain ethical standards in research.

9. Stay informed on emerging pharmacoepidemiologic methodologies and regulatory guidance.

10. Support the PI’s research goals with additional job-related tasks as assigned.

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

Bachelor's Degree

in Biostatistics, Statistics, Bioinformatics, Epidemiology, or related field

Required

Master's Degree

in Biostatistics, Statistics, Bioinformatics, Epidemiology, or related field

Preferred

PhD

in Biostatistics, Statistics, Bioinformatics, Epidemiology, or related field

Preferred

Demonstrated experience with statistical analysis and programming for research.

Required

Experience in data management, cleaning, & linkage of large healthcare datasets.

Required

Experience working with administrative healthcare claims data (Medicare, Medicaid, commercial insurance datasets) is highly desirable.

Required

Fluency in data management and statistical programming languages (SAS, SQL, R, STATA, or Python).

Required

Solid understanding of pharmacoepidemiologic study designs and causal inference methods for observational data analysis.

Required

Familiarity with drug coding systems (NDC, ATC), diagnosis and procedure codes (ICD, CPT).

Required

Exceptional written and verbal communication skills for scientific reporting and collaboration.

Required

Knowledge of regulatory requirements and guidance for pharmacoepidemiology studies (e.g., FDA, EMA) is highly desirable.

Required

High motivation and ability to work independently.

Required

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:

Other University Setting(s)

Location:

Standing/Walking

X

Sitting

X

Bending/Stooping

X

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

X

Loud noise levels

X

Marked changes in humidity or temperature

X

Microwave/Radiation

X

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.