Lupus Nexus Bioinformatics Scientist

Lupus Research Alliance Inc.•New York, NY

4d•Remote

About The Position

The Lupus Research Alliance [http://www.lupusresearch.org] (LRA) is the world’s leading non-governmental, non-profit funder of lupus research. Over the past 25 years, the LRA has invested over $270 million in lupus research in more than 660 research and clinical studies. This is an exciting professional opportunity to support a critical initiative for the lupus community. Be part of a team of LRA staff, academic and industry experts, and individuals living with lupus who envision and bring to life a unique infrastructure that integrates a patient registry with a linked biorepository and a data analytics platform. This resource, referred to as the Lupus Nexus (LNx), will expedite scientific discovery and clinical development and accelerate precision medicine in lupus, with the goal of transforming lupus care. Candidates for this position may be located anywhere in the United States, but must be able to work on core EST hours with occaisional travel to our NYC office. Position Summary The Lupus Nexus Bioinformatics Scientist will be part of the Lupus Research Alliance’s Research Department and plays an important role in supporting efforts across the Lupus Nexus. This role is responsible for building and managing scientific data pipelines to ensure the quality and integrity of scientific data, from data acquisition and processing through storage and release. This role involves providing guidance on best practices for scientific data analysis, supporting researchers in deriving insights from complex datasets, and maintaining high standards of data accuracy and reproducibility. The ideal candidate will collaborate with data scientists, researchers, and technical teams to establish robust data management protocols, streamline data sharing processes, and enhance data accessibility while safeguarding sensitive information.

Requirements

BS degree in immunology, biomedical data analysis, statistics, or a related field
10+ years of experience in scientific data analysis with extensive experience working with multi-omic/molecular data types.
Working knowledge of AWS environments, R Studio and Jupyter Notebook is required.
Demonstrated ability to think strategically when planning and managing responsibilities.
Hands-on, self-directed, detail-oriented, organized, and conscientious.
Must be able to work independently and prioritize and manage multiple activities within tight timelines.
Team player who can build excellent working relationships both internally and externally.

Nice To Haves

MS with 8+ years or PhD degree with 3+ years of relevant experience preferred.
Working knowledge of Nextflow, GitHub, and Docker a plus.

Responsibilities

Manage scientific data ingestion pipelines.
Manage and oversee scientific data ingestion pipelines, ensuring the accuracy, consistency, and completeness of scientific datasets from vendors and external researchers.
Oversee metadata management and data harmonization efforts to facilitate standardized data sharing. Contribute to the resolution and documentation of data queries as per the established LNx Data Governance and Management Plan.
Engage with key collaborators and business partners to identify data needs, improve data workflows, and enhance the usability of research data for the scientific community.
Contribute to the review and quality control assessments of scientific data by the LNx Scientific Review Committee.
Manage data access for research projects
Manage data access requests and review processes, ensuring compliance with governance policies while promoting responsible data sharing.
Create research project-specific datasets, address and document on-platform data queries and provide on-platform -omics data support for scientific users.
Collaborate with researchers, data scientists, and technical teams to support complex data analysis and visualization efforts. Collaborate on the conceptualization and development of new methodologies associated with these analyses and efforts.
Establish and manage procedures for maintaining scientific data provenance and governance.
Contribute to the development of policies and procedures to support the ethical and effective release of scientific data to researchers and registry participants, including data sharing compliance, data harmonization, and meta-data management.
Work with internal staff and external vendors to ensure the seamless integration and interoperability of clinical and research data across multiple platforms.