Research Data Analyst

University of California, San Francisco; San Francisco (CA); On-site; USD 75,000 - 110,000; Full time

Job summary

University of California, San Francisco invites applications for a data analyst role within the Division of Gastroenterology and Hepatology. The position involves gathering, analyzing, and interpreting diverse research data, designing studies, and developing instruments to support advanced hepatology research.

The candidate will prepare reports and visualizations, communicate results to a multispecialty team, and contribute to scientifically rigorous analyses.

Qualifications

• Bachelor's degree in related area or equivalent experience/training.
• Ability to work with others from diverse backgrounds.
• Self-motivated and able to work independently and in a team.
• Strong problem-solving and time-management skills.
• Demonstrated service orientation and organizational skills.
• Ability to manage multiple tasks and prioritize effectively.
• Strong quantitative training and data interpretation abilities.
• Experience with data management and basic analytics desirable.

Responsibilities

• Gather, analyze, and interpret a wide variety of research data.
• Design and conduct research, select data samples, and develop instruments.
• Prepare reports, charts, tables, and visual aids to communicate results.

Skills

Teamwork

Communication

Organization

Prioritization

Problem-solving

Independent work

Learning

Service orientation

Education

Bachelor's degree in related area

Tools

SQL

R

Python

MS Word, Excel, Access

Job description

Job Description

Involves gathering, analyzing, and interpreting a wide variety of research data. Designs and conducts research including selecting data samples, developing research instruments, analyzing collected information according to established statistical methods, and developing recommendations based on research findings. Prepares reports, charts, tables, and other visual aids to interpret and communicate data and results.

The Division of Gastroenterology and Hepatology in the Department of Medicine advances the understanding, diagnosis, and treatment of gastrointestinal and liver diseases. The division provides outstanding care to patients and has a longstanding reputation for excellence in hepatology research.

Qualifications

Required Qualifications

• Bachelor's degree in related area and / or equivalent experience / training.
• Demonstrated ability to work with others from diverse backgrounds.
• Self-motivated and works independently and as part of a team.
• Demonstrated problem-solving skills. Able to learn effectively and meet deadlines.
• Demonstrated service orientation skills.
• Strong organizational skills.
• Ability to efficiently manage a variety of different tasks at the same time.
• Ability to prioritize tasks appropriately.
• Strong quantitative training.

Preferred Qualifications

• Two (2) years of progressive programming experience or equivalent educational experience.
• Knowledge of data management systems, practices and standards. Significant experience using SQL, R, or Python.
• Knowledge relating to logical data design, data warehouse design, data integration or the management of web content or other unstructured data. Strong quantitative background preferably in biostatistics, statistics, econometrics, or related fields.
• Significant experience using MS Word, Excel, and Access.
• Establish analyzable data sets and document them for future use by statisticians. Perform range and quality checks and make recommendations to study staff for revising existing procedures to mitigate data errors.
• Demonstrated effective communication and interpersonal skills. Ability to communicate effectively with a diverse range of non-technical staff.
• Strong analytical and design skills, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems.
• Ability to represent relevant information in abstract models. Critical thinking skills and attention to detail.
• Experience with longitudinal regression modeling, sample size calculations.
• Experience in scientific writing for publication.