Data Scientist, Lupus Nexus

Lupus Research Alliance; New York (NY); Hybrid; USD 125,000 - 150,000; Full time

Job summary

The Lupus Research Alliance seeks a Data Scientist to support the Lupus Nexus data infrastructure, integrating a patient registry with a linked biorepository and analytics platform. The role involves managing and analyzing complex datasets, building data pipelines, and collaborating with researchers to translate questions into analyses.

The ideal candidate has strong programming skills, experience with clinical and omics data, and a track record of scientific writing.

Qualifications

• PhD in immunology, biomedical sciences, biostatistics, epidemiology, computational biology, bioinformatics, or related field, with 3+ years of relevant experience, or MS with 8+ years.
• Experience analyzing both clinical and multi-omic/molecular data. Experience with longitudinal clinical or real-world data strongly preferred.
• Working knowledge of R Studio and Jupyter Notebook required. Working knowledge of Nextflow and Docker a plus.
• Working knowledge of AWS environments, SQL, and GitHub or other version control is preferred.
• Proficiency in at least one programming language commonly used for scientific analyses (e.g., R, Python).
• Experience with observational research methods and with clinical or real-world data standards (e.g., OMOP or CDISC) preferred.
• Experience with immunology or autoimmune disease data preferred.
• Experience with human-subjects data under consent, IRB and privacy requirements.
• Demonstrated ability to think strategically, work independently, and manage multiple activities on tight timelines.

Responsibilities

• Oversees data analysis pipelines and data quality across datasets from vendors and researchers.
• Oversee metadata management and data harmonization for standardized sharing.
• Contribute to quality control assessments by the LNx Scientific Review Committee.
• Collaborate with internal staff and external vendors to integrate clinical and research data across platforms.
• Engage with collaborators to identify data needs and improve data workflows.
• Independently develop and execute code-based analyses of complex clinical, immunological, and multi-omics datasets.
• Develop reproducible workflows and document methods and outputs for transparency.
• Identify opportunities to leverage existing datasets to answer new questions.
• Support researchers in determining feasibility and inclusion/exclusion criteria.
• Serve as a scientific computational resource and contribute to abstracts/publications/reports.

Skills

Programming in R/Python

Clinical/multi-omics analysis

Scientific writing

Independent researcher

Education

PhD in immunology/biomedical sciences/biostatistics/epidemiology/computational biology

MS with 8+ years experience

Tools

R Studio

Jupyter Notebook

Nextflow

Docker

AWS

SQL

GitHub

Job description

Reports to: Lupus Nexus Director, Lupus Research Alliance

Location: Remote or Hybrid NYC

Salary: $125,000 - $150,000 (based on location and qualifications)

Background

The Lupus Research Alliance (LRA), the world’s largest non-governmental funder of lupus research, seeks a Data Scientist 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.

Position Summary

The Data 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 managing and analyzing complex scientific and clinical datasets to enable the generation of high-quality, reproducible research and biological insights by researchers accessing the LNx. The role will build and manage scientific data pipelines while also conducting code-based analyses of multi-omics, clinical, and biomarker data; interpreting findings in an immunological and disease context; and partnering directly with researchers to turn scientific questions into analytical approaches while maintaining high standards of data accuracy and reproducibility. The role may also lead or contribute to the publications and data reports that show what LNx data can answer. The ideal candidate will have strong computational and quantitative skills, demonstrated experience in independently analyzing complex biological datasets, and the scientific expertise necessary to evaluate such datasets relevant to research studies.

Responsibilities

Oversees scientific data analysis and quality

• Manage and oversee scientific data analysis 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.
• Contribute to the review and quality control assessments of scientific data by the LNx Scientific Review Committee.
• Work with internal staff and external vendors to ensure the seamless integration and interoperability of clinical and research data across multiple platforms.
• 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.

Conduct scientific data analyses and support biological discovery

• Independently develop and execute code-based analyses of complex clinical, immunological, and multi-omics datasets to support research questions from scientists (e.g., genomic, transcriptomic, proteomic, clinical data).
• Develop reproducible analytical workflows and document code, methods, assumptions, and outputs to support scientific transparency and reuse.
• Proactively identify opportunities to leverage existing datasets and pipelines to answer new scientific questions.
• Use the available clinical and scientific data to support researchers with determining feasibility and refining inclusion/exclusion criteria for research projects.
• Serve as a scientific computational resource for researchers, helping them understand how the available datasets can answer their scientific questions.
• Lead or contribute to abstracts, publications, and an annual data report that show what LNx data can answer.

Data governance, access, and compliance

• Manage data access requests and review processes, ensuring compliance with governance policies while promoting responsible data sharing.
• 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.
• Apply disclosure controls before results are released to researchers or participants.

Requirements:

Credentials & Qualifications:

• PhD in immunology, biomedical sciences, biostatistics, epidemiology, computational biology, bioinformatics, or a related field, with 3+ years of relevant experience, or MS with 8+ years.
• Experience analyzing both clinical and multi-omic/molecular data. Experience with longitudinal clinical or real-world data strongly preferred.
• Working knowledge of R Studio, Jupyter Notebook is required. Working knowledge of Nextflow and Docker a plus.
• Working knowledge of AWS environments, SQL, and GitHub or other version control is preferred.
• Proficiency in at least one programming language commonly used for scientific analyses (e.g., R, Python), with the ability to write, modify, debug, and maintain analytical code.
• Experience with observational research methods and with clinical or real-world data standards (for example OMOP or CDISC) preferred.
• Experience with immunology or autoimmune disease data preferred.
• Experience working with human-subjects data under consent, IRB and privacy (e.g., HIPAA) requirements.
• Demonstrated ability to think strategically when planning and managing responsibilities.
• Hands-on, self-directed, detail-oriented, organized, and conscientious.
• Able to explain data, methods, and limitations clearly to researchers.
• Strong scientific writing, including methods sections for abstracts and publications.
• 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.

The Lupus Research Alliance, Inc. is an Equal Opportunity Employer, committed to equal opportunity for all regardless of race, ethnicity, color, ancestry, national origin, citizenship, religion, sex, sexual orientation, gender identity/orientation/preference, class or socioeconomic status, marital status, age, ability, or Veteran status.