The positions requires interacting with project investigators, collaborators internal and external to Brown, other analysts, and a variety of research staff. Position responsibilities include the following:
to create study-specific data analysis files;
to develop and maintain core and study-specific analytic files;
to conduct analyses of research data (including large-scale administrative and motor vehicle driving data);
to assist in the preparation of reports, manuscripts and project-related technical writing; and
to generate metadata (i.e., data that provides information about the project datasets) as well as document and archive analytic files for future reference by investigators.
The positions also require good writing skills for summarizing the approaches employed to generate analytic output.
This position will involve working on one or both of the following National Institute on Aging-funded projects:
Clinically Significant Drug Interactions among Nursing Home Residents with Alzheimerâ™s Disease and Related Dementias (ADRD): This observational research will identify important drug interactions and examine their effects on fall-related injuries and other important outcomes among older nursing home residents with ADRD. The study will use innovative electronic health record (EHR) datasets from thousands of nursing homes as well as linked Medicare claims data, clinical assessment data, and several other unique datasets. Study findings will provide evidence that directly informs medication prescribing, deprescribing, and management to improve the safe use of medications among older adults with ADRD.
The risks and consequences of a motor vehicle crash in older adults with Alzheimer's Disease and Related Dementias: Older adults with Alzheimerâ™s Disease and related dementia disorders (ADRD) are at increased risk of a motor vehicle crash due to impairment of the cognitive and sensory functions necessary for safe driving. This study will use a novel data source of Medicare insurance claims linked to licensing, citation, and crash data for more than 1.5 million older drivers over a 13-year period to evaluate longitudinal changes in the risk of a crash and changes in the trajectory of health, health care utilization, and long-term care assistance following a crash, among older drivers with ADRD
Benefits and Harms of Long-term Osteoporosis Pharmacotherapy: Osteoporosis drug therapy reduces fractures that cause disability, entry into nursing homes, and premature death among older adults, but long-term exposure to many treatments for osteoporosis has been linked to serious, rare side effects. Better understanding of the benefits and harms of different long-term osteoporosis drug therapy strategies will help to guide treatment decisions for older adults and ultimately improve patient health outcomes. Additionally, the proposed work will establish a unique multinational data partnership that can be re-used to conduct timely observational studies on the effects of osteoporosis drug therapy in older adults.
About the principal investigators Drs. Zullo and Joyce:
Dr. Andrew Zullo (he/him/his) is a pharmacoepidemiologist focused on improving medication and vaccine use for older adults. He specializes in studying the outcomes of greatest importance to this population, such as physical and cognitive function, and has a particular interest in institutional post-acute care and long-term care.
Dr. Nina Joyce (she/her/hers) in an epidemiologist whose work focuses on the impact of policies to improve the safe-mobility of older adults and the advancement of methods for studying causes of motor vehicle crashes, particularly among older adults with dementia or other cognitive impairment.
Dr. Kaley Hayes (she/her/hers) is a pharmacoepidemiologist whose research goal is to optimize the use of medications for chronic conditions in older adults. She conducts research using advanced causal inference methods to examine real-world outcomes among older patients with osteoporosis, cardiovascular conditions, and diabetes.Â
Major Responsibility:Data Analysis. 40% of effort.
Supporting Actions:Â Operationalize study constructs, and validate empirical measures. Work with investigators in identifying and implementing analytic approaches appropriate for study aims, including regression models and machine learning algorithms, using common computational/statistical software programs.
Major Responsibility:Â Create and maintain project specific analytical files.Â 40% of effort.
Supporting Actions:Â Assist faculty in the design and development of databases for their studies. Assemble and link multi-layered, complex administative and research data to suit diverse research objectives.Â Assess data quality, and devise strategies to manage large data sets efficiently and to address limitations of available data.Â Â Provide full documentation of the program and data flow, variables created, and resulting database structure.
Major Responsibility:Â Write the methods sections of reports, assist in preparation of technical documents and manuscripts and maintain center data and analytic resource archive. 20% of effort.
Supporting Actions:Â Â Summarize, interpret, and report analytic results. Â Prepare research reports for internal and external organizations. Assist the Principal Investigators in writing technical documents and manuscripts for publication in peer-reviewed journals, and assist in preparation of research presentations.Â Maintain and expand clearly and concisely written internal online archive documenting all core data and analytic resources.
Section 4: Decisions Position is Free to Make
Prioritize multiple research activities
Manage multiple databases and analytic files, solving day-to-day analytic problemsÂ
Recommend strategies for managing data limitations
Collaborate with study team to develop analytic strategies
Co-author manuscripts and other documents to disseminate findings
Reports to as many as two of the following Principal Investigators (supervisors): Andrew Zullo, Nina Joyce, and/or Kaley Hayes.
Collaborates with remote colleagues at the Children's Hospital of Philadelphia, University of Pennsylvania, University of Toronto, and elsewhere.
Handles sensitive data from hundreds of thousands to millions of people provided to the project under data use agreements.
Responsibilities are multi-faceted, including data management, programming, and writing reports and manuscripts for publications.
Job Qualifications and Competencies
Education and Experience
Required: Bachelorâ™s degree in Biostatistics, Applied Mathematics, Economics/econometrics, Epidemiology, or equivalent quantitative disciplines, and 1-3 years related experience
Preferred: Masterâ™s degree in Epidemiology, Biostatistics, Applied Mathematics, Economics/Econometrics, or Public Health (no prior related experience required)
Data management and analysis experience.
SAS, R, or Stata programming knowledge, skills and experience, regarding both data management and analysis (note that data are stored in SAS datasets and thus some experience with SAS is required to extract study data, though any programming language can be used for data management and analysis).
Experience in data visualization techniques (i.e., effective use of charts and graphs to convey study findings).
Excellent computer skills: Microsoft Word, Excel and Power Point.
Excellent oral and written communication skills.
Willingness to collaborate with and learn from more senior analyst and other colleagues.
Proficiency with teleconferencing software (e.g., Zoom) and interacting with remote colleagues.
Ability to manage multiple tasks, set priorities, and meet deadlines.
Thoroughness, organization, and attention to detail, and ability to produce high-quality deliverables.
Possesses a willingness and ability to support a diverse and inclusive environment.
Demonstrated knowledge of the United States Health Care System, including standard healthcare coding systems such as International Classification of Diseases versions 9 and 10 (ICD-9 and ICD-10), Current Procedural Terminology (CPT), Healthcare Common Procedure Coding System (HCPCS), and Diagnosis Related Group (DRG) codes
Experience with ICD-9 to ICD-10 General Equivalence Mappings (GEMs) and Healthcare Cost and Utilization Project (HCUP) Clinical Classifications Software for Services and Procedures
Experience with CMS claims and beneficiary assessment data, particularly prescription drug claims (e.g., Medicare Part D), as well as familiarity with means of deriving adherence estimates from claims data
Experience with large-scale EHR data, particularly linked medication order and electronic medication administration record (eMAR) data
Experience with the use of census data (identifying the correct tables and creating analytic files at the correct geographic unit)
A demonstrated interest in learning about and becoming proficient in advanced methods like sequential target trial emulation, high dimensional propensity scores, and g-methods (marginal structural models, g-formula, and g-estimation)
Physical Demands and Working Conditions
Â General Physical Demands
Use of Chemicals
â˜’ Requires ability to read
â˜’ Typically less than 10 pounds
â˜’ Limited exposure to chemicals
â˜’ Must remain in stationary position for long periods of time at desk or computer
â˜’ Requires occasionally standing, sitting, walking; using hands to finger, handle, or feel objects, tools or controls; Â reaching with hands and arms; climbing stairs; hearing; talking
â˜’ Operates a computer and other office equipment
All offers of employment are contingent upon successful completion of a background check and education verification.
Recruiting Start Date:
Job Posting Title:
Senior Data Analyst
Center for Gerontology & Health Care Research
Fixed Term (Fixed Term)
Scheduled Weekly Hours:
Please note that in order to be considered an applicant for any staff position at Brown University you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
In order to maintain 90% or greater universal vaccination rates on campus, all newly hired employees at Brown University must receive the final dose of the COVID-19 vaccine before they begin work, unless they are approved for a medical or religious exemption. All employees must also receive a COVID-19 booster within thirty (30) days of becoming eligible. For more information, please visit the Healthy Brown site.
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