Position: Data Analyst (Early Career)

Location: San Diego, CA

Team: Unified Data Platform

Statistician/ Mathematician: TE.DAST.P3

About Neomorph

Neomorph is pioneering the discovery and development of molecular glue therapeutics — small molecules that selectively induce protein–protein interactions to degrade or modulate disease-causing targets. Our mission is to unlock a new class of medicines by combining cutting-edge biology, chemistry, and data science to solve some of the most challenging problems in drug discovery.

We operate at the intersection of experimental science and quantitative rigor. Data is central to our platform — from high-throughput screening and proteomics to structure-guided design and translational research. Our ability to extract insight from complex biological data directly accelerates therapeutic discovery.

The Role

We are seeking an early-career Data Analyst with strong quantitative training to support our scientific teams working in the molecular glue discovery space. Projects will focus on developing automated analysis methods that support large scale screening studies to identify new candidate compounds. This role is ideal for someone with a master’s degree in the mathematics sciences or related quantitative discipline who is excited to apply rigorous analytical methods to biological and experimental datasets. In this highly collaborative role, you will partner closely with biologists, and chemists, as well as receive mentorship from principal level data scientists.

What You’ll Do

• Analyze high-dimensional biological datasets (e.g., screening data, assay readouts)
• Develop reproducible workflows in Python, or similar tools to clean, transform, and analyze experimental data
• Apply statistical modeling and hypothesis testing to evaluate experimental outcomes
• Build dashboards and visualizations to communicate findings to cross-functional scientific teams
• Partner with scientists to translate research questions into analytical frameworks
• Contribute to building scalable data infrastructure and analytical standards across drug discovery programs

What We’re Looking For

• Master’s degree in the mathematics sciences (e.g., mathematics applied mathematics, operations research, statistics, data science)
• 0–3 years of professional or research experience (graduate research strongly valued)
• Strong programming skills in Python, R, or similar statistical languages
• Solid understanding of statistical inference, regression modeling, and experimental design
• Familiarity with SQL and working with structured datasets
• Ability to communicate quantitative findings clearly to scientific collaborators
• Passion for applying your quantitative skills set to scientific research, which has been demonstrated through course work, research, or prior work experience
• Eagerness to work collaboratively in a team-oriented environment

Nice to Have

• Exposure to biological data analysis (e.g., omics data, screening assays, bioinformatics)
• Experience with visualization tools or interactive dashboards
• Familiarity with machine learning approaches
• Exposure to software development tools (e.g., version control, IDEs, containerization, cloud services, project management)