Data Analyst, Science & Technology Platform

Data Analyst, Science & Technology Platform

United States, Massachusetts, Somerville

Ariadne Labs is a joint center for health systems innovation at Brigham and Women's Hospital and the Harvard T. H. Chan School of Public Health. Our goal is to drive scalable solutions for better care at critical moments in people's lives everywhere. Better care means better health outcomes, lower costs, and more actual caring. Critical means solving health systems failures that have major impact, typically touching people by the millions.

The Science and Technology Platform provides subject matter expertise in three scientific disciplines:
Computer science, data science, and implementation and improvement science. The Platform collaborates with teams across the Lab to deliver technology solutions and ensure projects meet high standards for scientific rigor. Under the supervision of the platform manager, the data analyst will lead data analysis and coordination activities for a multi-state public health research project evaluating the integration of genomic sequencing into newborn screening programs, as well as contribute to other ongoing Lab projects.

This includes developing and maintaining REDCap data systems, coordinating with study partners, applying advanced programming skills to manage and clean complex datasets, and conducting analyses in collaboration with research teams.

Ideal candidates will have strong experience working with quantitative data and an interest in applying their skill set to help solve health systems problems, particularly around the integration and use of genomics in healthcare. This is an excellent opportunity to apply and strengthen skills in data analysis, quantitative methods, and health systems research with flexibility to grow as a technologist, data scientist, researcher, and designer.

We are looking for individuals who embrace complex challenges and bring creativity and energy to solving them.

• Serve as the lead data analyst for a large, NIH-funded, multi-site feasibility study examining implementation of genomic newborn screening within existing state public health programs, spanning ~14 implementation sites, ~7 public health laboratories, and up to 30,000 newborns.

• Design, build, and maintain secure and scalable REDCap databases and data systems to manage complex, multi-source data streams.

• Coordinate with study partners and remote teams to design, implement, and maintain robust data systems that support the setup and ongoing operations of the study.

• Ensure data completeness, consistency, and integrity across multiple sites by developing and automating data quality checks and monitoring reports.

• Apply advanced programming techniques to clean and transform raw data into usable formats for analysis and reporting.

• Develop dashboards, reports, and visualisations to communicate findings to technical and non-technical stakeholders.

• Conduct exploratory and statistical analyses to identify trends, patterns, and correlations.

• Collaborate on other projects across Ariadne Labs by contributing to data-related activities as needed, including data collection, integration, cleaning, analysis, and visualization.

• Partner with cross-functional teams to scope requirements, design solutions, and support execution toward shared goals.

• Develop collegial relationships with collaborators, program leaders, and internal and external stakeholders.

A cover letter is required. Shortlisted candidates will be invited to complete a brief analysis exercise as part of the selection process.

• BA/BS required - preferably in Statistics, Data Science, Economics, Computer Science, Public Health, or a related field.

• 3-5 years of experience managing and analyzing complex health research datasets, preferably in multi-site clinical or public health studies.

• Expertise in REDCap, including project design, longitudinal data capture, data quality checks, and complex workflows.

• Strong critical thinking skills and exceptional attention to detail.

• Expertise in an analytical programming language (R or Python), with the ability to independently design, optimize, and…