We are seeking a highly skilled Data Scientist with deep expertise in modern AI/ML systems, including LLMs, multimodal models, fine-tuning techniques, and advanced retrieval architectures. In this role, you will design, prototype, and deploy AI-powered solutions that leverage state-of-the-art language, vision, and agentic frameworks. You will work closely with engineering, product, and research professionals across the US and Europe to bring cutting-edge AI capabilities into production environments. Your Responsibilities: - Design, build, and optimize LLM-powered systems using OpenAI, Anthropic, and open-source/local model families. - Architect and implement RAG pipelines, including hybrid search, query rewriting, prompt optimization, and reranking strategies. - Develop and maintain vector database infrastructures (Pinecone, Weaviate, Qdrant) for large-scale embedding storage and fast retrieval. - Train, evaluate, and retrain embedding models for domain-specific semantic search and knowledge retrieval. - Build and integrate multimodal AI solutions using OCR, CLIP, and modern vision architectures for text-image understanding. - Apply fine-tuning techniques (LoRA/QLoRA) to adapt foundation models to organizational datasets and specialized tasks. - Develop production-ready AI applications using Python, PyTorch, and modern orchestration frameworks. - Implement LLM orchestration with LangChain or LlamaIndex, including evaluators, tool abstractions, memory, and RAG components. - Establish robust evaluation frameworks to measure model performance, reduce hallucination, and ensure reliability in production. - Build agentic workflows using AutoGen, CrewAI, or similar frameworks to power automation and multi-agent collaboration systems. - Stay current with research trends and apply theoretical and practical insights in Generative AI to drive innovation across the organization. What we look for: - Experience in applied machine learning or data science, with at least 2 years focused specifically on LLMs or Generative AI. - Demonstrated experience building end-to-end RAG, fine-tuning, or multimodal AI systems. - Strong proficiency in Python, PyTorch, and AI tooling ecosystems. - Experience deploying models at scale in production environments. - Strong understanding of evaluation metrics, model reliability, and safety/reduction of hallucination. - Familiarity with vector embeddings, vector databases, and semantic search. - Experience with agent frameworks such as AutoGen, CrewAI, or LangGraph-like toolkits. - Experience with distributed training, model optimization, quantization, or GPU acceleration. - Knowledge of DevOps/MLOps tooling for deploying LLM-based systems. - Contributions to open-source LLM or RAG projects. What we offer: - Competitive salary and performance-based bonuses. - Fully remote, flexible work environment. - Modern laptop and hardware provided by us. - Specialized training in AI, automation, and digital productivity tools. - Global exposure—collaborate with top-tier founders and fast-growing startups. - Continuous learning and career growth opportunities in an international environment.

• Develops scalable software solutions utilizing statistical, artificial intelligence (AI) and machine-learning (ML) modeling approaches in support of Fraud, Waste, & Abuse (FWA) detection • Identifies, accesses, compiles, and uses internal and external sources of relevant data • Performs research and testing to develop machine learning algorithms and predictive models • Conducts and reviews model training and evaluation • Integrates, tests, tunes, and monitors solutions • Design and develop data models to predict member outcomes or future impact of key member decisions • Design and construct analysis tools that extract, and analyze data and store analytical results in an appropriate format for business needs • Conduct exploratory data analysis from complex data sources and build key data sets to support Centene’s mission • Evaluate and design experiments to monitor key metrics and identify improvement opportunities • Develop mathematical and statistical models to distinguish relevant content or events and recognize patterns • Participate in presentations and communicate results of analysis and findings • Participate in the design of automated, operational analytics processes to achieve scale and durability of analysis processes • Validate and measure the outcomes of health management programs using SAS, R and other tools, to include provider data, claims data, membership data • Manage multiple projects as assigned • Assist with training Data Analysts.

NEORIS es un acelerador Digital que ayuda a las compañías a entrar en el futuro, teniendo 20 años de experiencia como Socios Digitales de algunas de las mayores compañías del mundo. Somos más de 4,000 profesionales en 11 países, con nuestra cultura multicultural de startup en donde cultivamos innovación, aprendizaje continuo para crear soluciones de alto valor para nuestros clientes. Estamos en búsqueda de Data Scientist Principales responsabilidades: - Experto en analizar, interpretar y transformar datos en información accionable para la toma de decisiones estratégicas. Combina habilidades en estadística, programación y conocimiento del negocio para desarrollar modelos predictivos, identificar patrones y resolver problemas complejos utilizando datos. Requerimientos: - Experiencia entre 2 a 4 años como Data Scientist - Experiencia con lenguajes de programación como Python, R o Julia. - Conocimiento en herramientas y bibliotecas de aprendizaje automático (TensorFlow, Scikit-learn, PyTorch). - Experiencia en manejo de bases de datos (SQL, NoSQL) y herramientas de big data (Spark, Hadoop). - Competencia en estadística, probabilidad y matemáticas avanzadas. - Habilidades en herramientas de visualización (Tableau, Power BI, matplotlib, Seaborn). - Deseable un posgrado o certificaciones en Ciencia de Datos o campos afines. - Certificaciones recomendadas: Google Data Scientist Professional, Microsoft Certified: Data Scientist Associate o similares. Ofrecemos: - Salario competitivo. - Medicina prepagada. - NEORIS Days (3 días libres). - Fondo de Empleados. - Bonificación por cumplimiento anual. - Bono vacacional. - Herramientas corporativas. - Plataformas de capacitación y entrenamiento. - Trabajo remoto Te invitamos a conocernos en http://www.neoris.com, Facebook, LinkedIn, Twitter o Instagram: @NEORIS. Manuel Lunahuana (LI-ML2)

• Lead and Develop: Build, lead, and mentor a high-performing team of data scientists focused on the Marketing & Business Development domain. • Drive Strategy: Serve as a thought-partner to cross-functional leaders (Product, Engineering, Design, and Marketing), communicating and shaping the roadmap and strategy for Reddit by identifying actionable and impactful insights. • Deliver Causal Insights: Lead initiatives to quantify the true incremental lift of marketing spend and prevent budget allocation on non-incremental channels, including developing and deploying Incremental/Predictive LTV models. • Standardize Measurement: Oversee the establishment of measurement frameworks (incl. effective experimental designs and/or Causal inference methods) to evaluate Brand Initiatives and ensure consistent metrics are aligned across the organization for campaign quality and ROI. • Drive Adoption: Drive the adoption of strategic and tactical recommendations based on deep product experience and data understanding to maximize our value to consumers. • Ensure Data Quality: Take a keen interest in the collection and quality of underlying data, including overseeing work on ETLs, reporting dashboards, and data aggregations needed for business tracking and/or ML model development. • Enable Self-Service: Lead initiatives to enable analytics self-serve capabilities for cross-functional teams.