Role Description 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. - 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. Qualifications - BS/MS in Cheminformatics, 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. - Working knowledge of Python for scientific data analysis, automation, and workflow support, including experience with libraries such as pandas, numpy, scipy, and matplotlib. - Strong expertise in SQL, including building and querying custom tables for internal workflows. - Strong problem-solving and data analysis skills with the ability to communicate scientific insights effectively. - Experience working with large, real-world scientific or laboratory datasets. - Familiarity with Linux environments and version control tools (e.g., Git). Requirements - Exposure to machine learning methods such as clustering, regression, or pattern recognition is a plus. - Exposure to cheminformatics or scientific software tools (e.g., RDKit, Spotfire, MOE, Schrodinger) is a plus. Benefits - Compensation: $120,000 – $182,000 annually, depending on experience. - Participation in the Company’s stock option plan. - 3% retirement safe harbor contribution. - Fully paid health, dental, and vision insurance for employees, spouses, partners, and families. - Above-market life insurance and disability coverage. - Additional benefits to explore during the offer process.

• Pré-processamento e enriquecimento de textos: Limpeza, tokenização, lematização e remoção de ruídos em documentos textuais. • Geração e gestão de embeddings: Criar embeddings de documentos e consultas usando modelos como Sentence‑BERT, OpenAI ada ou similares. • Construção de pipelines de busca semântica, recuperação de informação e aplicações com RAG: Desenvolver pipelines que combinam: consulta → embedding → busca vetorial → re-ranking (opcional) → uso do contexto recuperado em aplicações com RAG. • Adaptação e experimentação com modelos em PyTorch ou TensorFlow: Utilizar modelos pré-treinados e adaptá-los para tarefas específicas. • Documentação e versionamento: Documentar pipelines, decisões técnicas e resultados de experimentos.

• Own the data lifecycle from ingestion to delivery • Build and maintain crawlers, API integrations, and vendor data feeds • Monitor collection reliability and onboard new data sources • Manage the full data pipeline from raw to production • Implement automated QA at every stage • Maintain schema integrity in BigQuery and PostgreSQL • Ensure downstream consumers receive consistent, documented datasets • Document every transformation rule and edge case • Contribute to building a data product that external customers pay for

• Architect and ship production-grade LLM applications • Design RAG pipelines that actually work at scale • Collaborate closely with product and engineering to own problems end-to-end • Design, build, and deploy AI models, tools, and agents • Partner with the Head of Data & AI to define the technical architecture • Implement retrieval augmented generation (RAG) pipelines • Design and implement Model Context Protocol (MCP) integrations • Build and maintain MCP servers • Establish patterns for MCP host/client configuration, access control, and observability • Implement MLOps and LLMOps practices • Collaborate with data engineers and platform teams