GeneDx (Nasdaq: WGS) delivers personalized and actionable health insights to inform diagnosis, direct treatment, and improve drug discovery. The company is uniquely positioned to accelerate the use of genomic and large-scale clinical information to enable precision medicine as the standard of care. GeneDx is at the forefront of transforming healthcare through its industry-leading exome and genome testing and interpretation services, fueled by the world’s largest, rare disease data sets. For more information, please visit www.genedx.com.

SUMMARY

The Process Improvement Analyst plays a critical role in supporting the Process Improvement and Commercial laboratories by building and maintaining tools and dashboards for quality monitoring of wet lab assays and providing data-driven insights. This role focuses on extracting, analyzing, and visualizing data to support the laboratory’s technical operations, ensuring optimized workflows, robust troubleshooting, and continuous improvement. The analyst will collaborate cross-functionally with technical operations, wet lab teams, and product to deliver actionable insights that enhance laboratory performance and efficiency.

EDUCATION, EXPERIENCE, AND SKILLS

• Bachelor’s degree in a scientific field (e.g., Biology, Chemistry, Genetics, or a related discipline), Data Science, Bioinformatics, Computer Science, Statistics, or equivalent practical experience.
• 3-4 years of experience in data analysis, visualization, or a related field, preferably in a laboratory or clinical operations environment.
• Demonstrated ability to design and implement tools for performance monitoring and decision support.
• Strong problem-solving skills with the ability to ensure accuracy of the data.
• Proven ability to manage multiple projects and deliver results under tight deadlines in a dynamic environment.
• Experience identifying operational efficiencies to streamline workflows.

• Proficiency in querying relational databases with SQL.
• Familiarity with laboratory data systems, such as Laboratory Information Management Systems (LIMS), and data structures.
• Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
• Knowledge of programming languages like Python or R for advanced data analysis is a plus.
• Hands-on experience in a laboratory setting, with an understanding of laboratory workflows, is strongly preferred. Previous exposure to clinical, scientific, or genetics environments is highly desirable.