Job Description

We are looking for a candidate who has solid practical experience with Neo4j, data modeling in graphs, optimization of Cypher queries and a strong collaboration with AI/ML teams and data engineering.\nNOTE: This post is open to candidates from Latam.\nKey Responsibilities\nDesign and implement Neo4j-based knowledge graph architectures to support Yotta's biological and biomedical reasoning work flows.\nDevelop robust graph data models that represent entities such as genes, proteins, biological pathways, phenotypes, illnesses, experimental conditions and spatial flight variables.\nBuild and optimize Cypher queries for relationships biological complexes of multiple jumps and hypothesis exploration.\nIntegrate Neo4j with AI/ML pipelines, including vector databases, embeddings, RAG/GraphRAG workflows and inference engines.\nSupport the ingestion of structured and semi-structured data from different sources (omics, publications, ontologies, APIs and internal datasets).\nImplement performance and scalability optimization strategies for large and constantly evolving graphs.\nCollaborate with data scientists, bioinformaticians and platform engineers to align the graph design with subsequent analyzes and their needs users.\nContribute to documentation, best practices and architectural decisions to guarantee the long-range maintenance of the platform.\nSupport security considerations, access control and data governance within the graph layer.\nMandatory Requirements\nReside in Latam.\nAdvanced level of English.\nMore than 3 years of practical experience developing with Neo4j in production environments.\nSolid experience in modeling data in graphs and designing databases centered on relationships.\nDomain of the Cypher query language, including optimization and profiling.\nExperience integrating Neo4j With backend services (Python, Java or similar). Desireables\nExposure to AI/ML systems, vector databases, embeddings or GraphRAG architectures.\nExperience deploying Neo4j in cloud environments (AWS, GCP or Azure).\nKnowledge in role-based access control (RBAC) and graph-level security models.\nPrevious experience as Sr Data Scientist.\nDesired Experience\nExperience with biological, biomedical or life science data (for example, genomics, proteomics, biological pathways, disease ontologies).\nFamiliarity with ontologies and standards (GO, MeSH, MONDO, Reactome, SNOMED, among others).\nPrevious experience supporting research platforms investigation or discovery.\nWhat can we offer?\nBe part of an international and multicultural company that promotes diversity.\nParticipate in international projects with a presence in North America, Pakistan, India and Latam.\nWork environment with expanded experience in remote and distributed work, using agile methodologies.\nCulture of continuous learning and development in current technologies.\nPleasant and collaborative environment, focused on team work.\nAccess to learning platforms, Google Cloud certifications, Databricks, Tech Talks, among others.\nActive participation in several internal and external innovation initiatives, hackathons, technology, agility, charlas, webinars, bienestar and culture, with the possibility on the ground to attend, but also to be an exhibitor.\nCompetitive salary in Chile (Chilean pesos), Colombia (Colombian pesos), Peru (soles) and LATAM (dollars)",