Data Analyst I

GENERAL SUMMARY/ OVERVIEW STATEMENT:

The Data & Informatics team at Massachusetts General Hospital is seeking a full-time Data Analyst for a functional multi-omics subgroup led by Rachel Buckley, PhD. We are a large multidisciplinary clinical Alzheimer's disease research group spread across Mass General Brigham, focusing on early detection and prevention strategies of Alzheimer's disease and related neurocognitive disorders. Our group runs multiple longitudinal cohort studies (e.g., Harvard Aging Brain Study) with rich neuroimaging, plasma biomarker, and neurocognitive phenotypes. We also work closely with secondary data from other studies across the United States. The successful candidate will help to establish and maintain genomic and transcriptomic data quality control pipelines, both single-cell and bulk tissue (brain and plasma), and will participate as a co-author in various scientific projects linking multi-omics data with neuroimaging and clinical phenotypes related to Alzheimer's disease progression. As a data analyst in a functional genomics subgroup, the successful candidate will have opportunites for presentations/publications if desired. The successful candidate will also have access to the communities and meetings of the Broad Institute of MIT and Harvard, a leading genomics institution. Although the primary responsibility of this position will be to genomic/transcriptomic data management and analysis, the successful candidate will also work closely with the Harvard Aging Brain Study Data & Informatics team, to facilitate harmonized omics and phenotype data management. We see the skills that will be developed in this job as allowing the future candidate to successfully progress towards PhD programs or industry in relevant fields (e.g. computational biology, neuroscience, applied statistics).

PRINCIPAL DUTIES AND RESPONSIBILITIES:

1. Establishment, maintenance, update, and documentation of omics data processing (quality control) pipelines for ongoing multi-omic data generation projects.

2. Working with investigators to coordinate relevant data generation/acquisition/transfer procedures.

3. Rapid assembly and manipulation of omics and phenotype datasets for analysis.

4. Implementation of bioinformatics analysis plans to produce results for publication and conference dissemination for other lab personnel.

5. Researching, assessing, and implementing novel bioinformatics models and approaches.

6. Working with investigators to develop and implement data analytics and visualizations in service of research aims.

7. Provide consultation and drafting of omics-related methods and results sections for manuscripts in collaboration with researchers.

SKILLS/ABILITIES/COMPETENCIES REQUIRED:

• Advanced computer skills, with the ability to manipulate large and varied datasets. (e.g., proficiency with Python and/or Unix shell scripting preferred).

• Proficiency with R.

• Prior experience in computational biology/bioinformatics (e.g., PLINK, RNA-Seq alignment tools, R Bioconductor, etc.) is strongly preferred, but not necessary if the applicant has the necessary programming experience.

• Experience with cluster computing is strongly preferred, but not essential.

• Demonstrable statistical and data analysis skills.

• Must be highly motivated and well-organized, personable, and empathetic with team members.

• Level of responsibility and maturity to work under pressure and meet the requirements of clinical research neuroscience laboratory.

• Very detail-oriented and highly organized.

• Ability to work independently and as part of a team.

EDUCATION:

B.A., B.S. required. Master's level candidates are preferred, particularly with training in the fields of computational biology, bioinformatics, computer science, biostatistics, applied mathematics or statistics. Individuals without formal training in these areas, but with the requisite experience and desired core skills will also be considered.

EXPERIENCE:

1 years of experience is preferred. Experience through coursework or undergraduate/graduate research projects is applicable.