Company Overview: Terray Therapeutics is a venture-backed biotechnology company where scientists and engineers build together to transform how small-molecule drugs are discovered and developed. By combining our nanotechnology, experimental science, machine learning, and automation, we leverage Terray’s ability to generate and learn from scale proprietary chemical data to discover novel medicines for patients in need.
At Terray, you will work alongside pioneers and experts in artificial intelligence, chemistry, drug discovery, automation, and nanotechnology in deeply interconnected workflows where computational and experimental teams continuously learn from one another. Our platform, EMMI (Experimentation Meets Machine Intelligence), powers iterative cycles of molecular design and wet-lab experimentation that rapidly improve our understanding of biochemical interactions and guide the next generation of discoveries.
Our teams support both an internal immunology pipeline and partnerships across a broad range of therapeutic areas. The work here is highly collaborative, fast-moving, and grounded in the belief that breakthroughs happen when strong science, thoughtful technology, and great people work closely together.
Position Summary: Terray is currently seeking a motivated and creative senior associate data scientist. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will be responsible for analyzing and visualizing data from our computational discovery platforms.
The core responsibilities of this position are:
- Collaborate with project teams in applying platform tools to identify and prioritize hits for follow-up synthesis, testing, and pipeline progression
- Work closely with computational and assay teams to perform hit validation analyses to evaluate how tArray platform binding profiles translate to off-platform assays
- Partner with screening teams to develop and refine target-specific screening strategies
Experience and Qualifications: Part of Terray's success is nurtured by a hands-on work environment where everyone is accountable, vested in a vision of excellence, and actively taking part in the success of the business. Terray supports a positive work environment where employees can feel engaged, recognized, and empowered to be creative.
Required Qualifications:
- BS/MS in Cheminformatics, Pharmaceutical Chemistry, Medicinal Chemistry, Computational Chemistry, data science or a related scientific discipline with a strong interest in programming and data-driven research
- Understanding of chemical structures, molecular properties, and compound profiling in the context of high-throughput screening and hit identification
- Experience with cheminformatics or scientific software tools (e.g., RDKit, Spotfire)
- Strong problem-solving and data analysis skills with the ability to communicate scientific insights effectively
- Working knowledge of Python for scientific data analysis, automation and workflow support including experience with libraries such as pandas, numpy, scipy and matplotlib
- Knowledge of SQL for querying custom tables for internal workflows
- Familiarity with Linux environments and version control tools (e.g., Git)
- Exposure to machine learning methods such as clustering, regression, or pattern recognition is a plus
Compensation Details: $120,000 – $182,000 annually, depending on experience. Terray’s salary ranges are designed to be competitive and are benchmarked against market base salary plus bonus within our industry and market. We align pay to role scope, skill level, and impact.
We invest heavily in benefits because taking care of our people matters. Our programs are benchmarked at the top of the Southern California market and designed to provide meaningful support across every stage of life. Benefits include participation in the Company’s stock option plan, a 3% retirement safe harbor contribution, fully paid health, dental, and vision insurance for our employees, spouse, partner, and families, as well as above-market life insurance, disability coverage, and much more to explore during the offer process.
