Biostatistician II (Health Economics/Decision Science section)

Beth Israel Lahey Health • Boston, MA

6d • $80,000 - $130,000

About The Position

When you join the growing BILH team, you're not just taking a job, you’re making a difference in people’s lives. The Health Economics Section of the Richard A. and Susan F. Smith Center for Outcomes Research at Beth Israel Deaconess Medical Center, led by Dr. Dhruv Kazi, is seeking a highly motivated and experienced biostatistician to join our team. Our group is devoted to addressing the most pressing questions in cardiovascular medicine and population health using state-of-the-science methods in epidemiology, economics, and decision science. Our work examines the real-world comparative effectiveness and cost-effectiveness of novel strategies for cardiovascular prevention, including their impact on long-term health and economic outcomes. To do so, we apply advanced statistical, econometric, and epidemiological methods to large datasets such as healthcare claims, electronic health records, and epidemiologic cohorts. Our work on the value and affordability of cardiovascular interventions has helped millions of individuals access high-quality, affordable care. The Biostatistician II will engage in a variety of collaborative research projects working closely with clinician investigators, fellow statisticians, administrative staff, and trainees. As a Biostatistician II you will have a key role in helping to produce high-impact research. You will carry out select data management and analytic activities for a variety of projects. Hands-on experience using SAS (Base, Stat, Macro, SQL) and R or Spark R working with large datasets is expected. Prior experience with administrative (Medicare/VRDC) claims data and electronic health record data (especially Truveta data, www.truveta.com) is highly preferred. In addition to traditional biostatistical methods such as regression, survival analyses, longitudinal analysis, preferred qualifications include experience with applying advanced causal inference methods in large real-world observational datasets. This includes a deep understanding of at least some of the following methods: target trial emulation, difference-in-differences, instrumental variable approach, or propensity score methods (adjusting, matching, weighting, stratification). This is an exceptional opportunity to work with a collegial and ambitious team of clinical, statistical, and epidemiological researchers whose work is regularly published in high-impact journals like Circulation, JACC, and JAMA Cardiology presented at major national and international conferences cited in clinical guidelines and influential in shaping drug pricing, coverage decisions, and health policy.

Requirements

• Master's degree in Public Health, Epidemiology, Statistics, Biostatistics or related field required.
• 3-5 years related work experience required.
• Demonstrated ability to work with software programs including SAS, Access, Powerpoint, Epi Info and Excel.
• Ability to conduct and interpret multivariable regression analysis.
• Documented ability to manipulate complex, large databases including Medicare and other insurance claims data.
• Advanced skills with Microsoft applications which may include Outlook, Word, Excel, PowerPoint or Access and other web-based applications. May produce complex documents, perform analysis and maintain databases.

Nice To Haves

• Hands-on experience using SAS (Base, Stat, Macro, SQL) and R or Spark R working with large datasets is expected.
• Prior experience with administrative (Medicare/VRDC) claims data and electronic health record data (especially Truveta data, www.truveta.com) is highly preferred.
• In addition to traditional biostatistical methods such as regression, survival analyses, longitudinal analysis, preferred qualifications include experience with applying advanced causal inference methods in large real-world observational datasets.
• This includes a deep understanding of at least some of the following methods: target trial emulation, difference-in-differences, instrumental variable approach, or propensity score methods (adjusting, matching, weighting, stratification).

Responsibilities

• Assists in the design, development and maintenance of data collection instruments, databases and procedure manuals.
• Designs, implements, and performs data management and quality control procedures as necessary for routine and special projects.
• Writes computer programs to combine data from separate computer files to allow comparison of data from different sources.
• Support the creation applications in support of research projects.
• Collaborates with program staff on the design and analysis of biostatistics aspects of research protocols.
• Participates in the design of questionnaires and interview forms.
• Analyzes data beginning with univariate and multivariate analyses such as logistic regression and factor analysis for research studies.
• Supports the interpretation and assist in the creation of study results in collaboration with faculty members, epidemiologists, biostatisticians and other team members.
• Provides tabular and graphic summaries of analyses in a form suitable for inclusion in manuscripts for publication in peer reviewed scientific journals as well as for presentation at scientific meetings

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees