Data Management Specialist II, Center for Human Brain Variation

The Broad Institute of MIT & Harvard is looking for an outstanding Data Management Specialist to provide comprehensive data management support for the Center for Human Brain Variation . The mission of the Center is to address an unmet need in cell census research: to understand the cell-type-specific mechanisms and larger tissue-level biological principles that generate meaningful variation in brain biology among people.

We are looking for a data management professional who is passionate about the mission of the Broad Institute and Center for Human Brain Variation. The ideal candidate will be highly collaborative and be prepared to lead and take direction as part of cross functional project teams. The candidate must be comfortable working with a high volume of single-cell datasets across multiple data management systems.

Responsibilities

• Advance large single-cell and spatial transcriptomic datasets through analysis workflows.
• Plan and execute analytical processes by which high-volume experimental data are quickly assessed for quality.
• Present key data quality metrics to scientific teams generating the data; provide regular updates to the project team at weekly lab meetings.
• Communicate complex quality metrics to stakeholders with different areas of expertise; develop presentation content appropriate for a variety of audiences.
• Coordinate the submission of large datasets to the appropriate data repositories (ie NeMO, NDA) and other key constituencies, while ensuring compliance with applicable policies such as the NIH Data Sharing Policy.
• Work with project managers and researchers to ensure that single-cell libraries are tracked and reviewed for quality in NIMP (Neuroanatomy-anchored Information Management Platform).
• Serve as the main point of contact for consortium data releases, working in close collaboration with other consortium members and sites.
• Work with software engineers toward optimization of analysis workflows for high-data-volume experiments.
• Collaborate closely with laboratory and data analysis teams to support overall project deliverables, ensuring deliverables are met on time.
• Provide a variety of reports summarizing research data usage. Assist the lab’s scientific teams in utilizing disk and cloud storage in cost-efficient and time-efficient ways.
• Assist the managing director with the preparation of progress reports that involve data deliverables.

Qualifications

• Bachelor’s degree in bioinformatics, computer science or a related field
• 1-2 + years of experience working in a high-data-volume scientific environment, including experience advancing data sets through complex analysis workflows
• Experience working with databases
• Working knowledge of at least one scripting language (ie. Python, R)
• Experience working in Linux operating system, including working knowledge of Bash, is preferred
• Familiarity with Google Cloud and/or AWS (Amazon Web Services)
• Experience with Next. Flow a plus
• Ability to thrive in a fast-paced rapidly changing environment
• Excellent organizational skills and ability to prioritize tasks thoughtfully
• Expertise in using Google Docs and Google Sheets
• Experience creating and managing reports (e.g. trend analysis, summary reports)
• Familiarity with single-cell technologies is preferred; for example, understands the entire 10X workflow from sample preparation through data analysis
• Experience working with sequencing output data, including BAM files and fastqs, is strongly preferred
• Comfortable learning new software and technologies
• Must possess a demonstrated ability to interact with an interdisciplinary group of both professional staff and academic trainees; including project managers, data analysts, computational scientists, and laboratory scientists

The expected base pay range for this position as listed above is based on a 40 hour per week schedule. Broad provides pay ranges representing its reasonable and good faith estimate of what the organization reasonably expects to pay for a position at the time of posting. Actual compensation will vary based on factors including but not limited to, relevant skills, experience, education, qualifications, and other factors permissible by law.