Data Entry Coordinator II
Salary$18 – $25/hr
LocationSaunders Research Building
Also in265 Crittenden Blvd, Rochester, New York, United States of America, 14642
Work modeon-site
Typefull-time
SeniorityMid
Department400990 Clin & Trans Science Institute
Company size10,000+ people
PostedOct 6, 2026 · 1w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Analyze social media data using computer vision and large language model and statistical analysis software such as Python, SQL, SAS or R
Conduct literature search on tobacco products and their association with health conditions and symptoms
Generate tables and figures for manuscript and conference presentations
Analyze electronic health record data using advanced statistical and machine learning models
Analyze national survey data using advanced statistical, machine learning, and deep learning algorithms
Skills
Python
SQL
SAS
R
About the company
As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever Better. Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect, and accountability. Together, we will set the highest standards for how we treat each other to ensure our community is welcoming to all and is a place where all can thrive.
Job Location (Full Address):
265 Crittenden Blvd, Rochester, New York, United States of America, 14642
Opening:
About the role
Worker Subtype:
Regular
Time Type:
Full time
Scheduled Weekly Hours:
40
Department:
400990 Clin & Trans Science Institute
Work Shift:
UR - Day (United States of America)
Range:
UR URG 103 H
Compensation Range:
$18.00 - $25.14
Legal
The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates will be set within the job’s compensation range, and will be determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.
Responsibilities:
Organization: The University of Rochester Clinical and Translational Science Institute Informatics Core provides comprehensive informatics infrastructure and expertise to support the full spectrum of clinical and translational research. The Core offers secure access to and integration of clinical, research, and populationlevel data; advanced data management and harmonization services; and analytic support spanning biostatistics, real-world data, and multi-omics integration. It enables investigators to efficiently identify cohorts, manage and analyze complex datasets, and develop reproducible, scalable workflows while adhering to regulatory, privacy, and security standards. By partnering closely with research teams from study design through dissemination, the Informatics Core accelerates discovery, facilitates cross-disciplinary collaboration, and strengthens the translation of data-driven insights into clinical and public health impact.
Position Summary: This position involves analyzing the social media data (e.g. Twitter, Reddit, Instagram, TikTok, and YouTube data) associated with either 1) emerging tobacco products and their associations with health conditions and symptoms, as well as public opinion on the government policies related to the emerging tobacco products or 2) electronic cigarettes and other tobacco products and their associations with social media user engagement. This includes analyzing social media data using computer vision and large language model and statistical analysis software such as Python, SQL, SAS or R, conducting literature search on tobacco products and their association with health conditions and symptoms, generating tables and figures for manuscript and conference presentations. The candidate will work under the general supervision of Dr. Li.
ESSENTIAL FUNCTIONS Conduct literature searches
•
Conduct literature search for statistical data analyses.
•
Summarize literature search into reportable paragraphs.
Analyze electronic health record and national survey data
•
Analyze electronic health record data using advanced statistical and machine learning models.
•
Analyze national survey data using advanced statistical, machine learning, and deep learning algorithms.
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