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- Responsible for data management and statistical analysis for new and ongoing studies.
- Job duties require applicant to have strong working knowledge of regression modeling and epidemiological study design and knowledge of R and related data analysis pipelines.
- Responsibilities include managing large-scale dataset and both developing and applying regression based analyses of epidemiologic and epigenetic data.
- Collaborate with PI, Center staff, and site PIs in performance of the above duties.
- Collaborate on the preparation of grant applications, manuscripts, and presentations.
- Understanding of data management and data analysis workflows.
- Knowledge of statistical analysis approaches (e.g., linear and logistic regression; longitudinal analyses) and epidemiological study design.
- Proven ability to learn new computational tools and packages.
- Interest in the identification and validation of biomarkers of mental health risk
- Ability to work independently, as well as part of a team in a fast-paced, highly collaborative, and supportive environment.
- Excellent written and verbal communication communications skills.
- Ability to adapt to shifting priorities in response to changing deadlines and the needs of the lab.
- Ability to handle multiple projects simultaneously.
- Ability to perform complex statistical analyses, data mining, database management, and computer programming (e.g., R, Unix)
- Bachelor's Degree required.
- Master's Degree preferred.
- One year of data analysis experience is strongly preferred.
Data Analyst I - Boston, United States - Massachusetts General Hospital
Description
General Summary/ Overview StatementThe Psychiatric and Neurodevelopmental Genetics Unit (PNGU) of the Massachusetts General Hospital (MGH) has an immediate opening for a Data Analyst, working under the direction of Dr. Alexandre Lussier. Dr. Lussier's research laboratory is housed in the Center for Genomic Medicine (CGM) and Department of Psychiatry. Research in the Lussier Lab is focused on identifying the social and biological determinants of mental health through studies on (1) the impact of early-life stressors, such as prenatal alcohol exposure and childhood adversity, on trajectories of mental health and resilience; (2) genomic and epigenomic predictors of psychopathology; and (3) gene-environment interactions, or how genetic mechanisms modify the effects of life experiences on risk for mental illness across the lifespan.
The Lussier lab is a highly collaborative research team that leverages large-scale human data and interdisciplinary approaches to investigatewhenandhowearly-life environments influence mental health, with the ultimate goal of identifying ways to predict and prevent mental illness. We at the Lussier lab firmly believe that this goal, and science in general, is strengthened by the inclusion of diverse voices and perspectives. We recognize that diversity manifests in many different ways, including differences in background, life experiences, training, etc. As such, we encourage candidates from underrepresented backgrounds to work with us.
The Lussier lab is seeking a Data Analyst to assist with translational research projects related to mental health and epigenetics. Candidates must have a BA/BS (MA/MS preferred), 1-2 years of experience, good quantitative skills, an ability to work well in a collaborative environment, fluency with all modes of communication in English, and strong writing skills. The ideal candidate will have strong scientific background, excellent programming skills using R, advanced knowledge of statistical methods, and expertise in the analysis and interpretation of epidemiologic, genomic, and/or longitudinal data is preferred.
Candidates will gain valuable experience and knowledge working in all phases of the research process, ranging from study design to the analysis and interpretation of results. Opportunities to co-author manuscripts and present study results at conferences may be available. Finally, candidates will have the opportunity collaborate with world-class researchers at MGH, Harvard, and beyond, and will closely interact with members the Dunn lab in the PNGU. Hybrid or remote work opportunities are available.
Principal Duties And Responsibilities
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