• Support a business team’s ability to leverage data in support of business monitoring and decision management • Perform data exploration and analysis to identify and interpret trends and patterns in datasets • Create dashboards, visualizations, and reports to support business performance monitoring • Work collaboratively with the enterprise analytics & information management team to articulate business needs • Contribute to data inventory and stewardship efforts, including contributions to metadata management, data profiling, data quality remediation, and data cleansing • Perform user acceptance testing to confirm data output and capabilities meet business expectations and align to business processes • Troubleshoot data discrepancies and inconsistencies

Role Description Como Technical Data Scientist Manager, sua missão será de responder pelo entendimento técnico do problema e corresponsável pela entrega, atuando como ponto focal técnico junto ao cliente e no acompanhamento e desenvolvimento da carreira da equipe com o objetivo de agregar valor ao projeto, cliente e time, topa? Vamos nessa! Qualifications - Experiência em liderança técnica de equipes de Ciência de Dados e IA. - Sólido conhecimento em Inteligência Artificial Generativa. - Experiência prática com Large Language Models (LLMs), incluindo modelos proprietários e open source. - Experiência no desenvolvimento de agentes de IA (AI Agents) utilizando frameworks como LangGraph, CrewAI, AutoGen, Semantic Kernel ou similares. - Conhecimento em arquiteturas de agentes, incluindo planejamento, uso de ferramentas (tool calling), memória, orquestração de fluxos e agentes colaborativos. - Experiência na construção de soluções baseadas em RAG (Retrieval-Augmented Generation). - Conhecimento em engenharia de prompts e avaliação de respostas de LLMs. - Experiência com bancos vetoriais. - Experiência com frameworks para desenvolvimento de aplicações com LLMs, como LangChain, LlamaIndex ou equivalentes. - Conhecimento em Python e bibliotecas para IA. - Experiência com APIs REST e integração de sistemas. - Conhecimento em MLOps, versionamento e monitoramento de modelos de IA. - Experiência em ambientes de nuvem (Azure, AWS ou GCP). Requirements - Definir a arquitetura da solução baseada em LLMs e agentes inteligentes. - Projetar agentes especializados para consulta, interpretação e análise de informações. - Implementar estratégias de RAG para consulta segura e contextualizada de documentos técnicos. - Definir mecanismos de memória, contexto, planejamento e uso de ferramentas pelos agentes. - Avaliar continuamente o desempenho dos LLMs por meio de métricas como precisão, groundedness, relevância e alucinação. - Liderar a evolução da arquitetura de IA, incorporando novos modelos, técnicas e boas práticas. Benefits - Horário flexível; - Estrutura horizontal; - Programas de treinamento e desenvolvimento; - Cultura voltada para a Diversidade & Inclusão, onde você pode ser livre pra ser quem é! Company Description Quer conhecer melhor o CESAR? Clica aqui e vem com a gente!

Environmental Data Analyst Location: Olympia WA United States Job Description: Salary Range $76,000.00 - $110,000.00 Salary/year Position Type Full Time Education Level Bachelors Degree GSI is seeking an Environmental Data Analyst who combines technical ability, analytical creativity, and business acumen to strengthen our data management, analysis, and visualization team. The ideal candidate is comfortable across the full data lifecycle-building and maintaining relational databases, developing analysis and automation pipelines in SQL, Python, and/or R, and providing query, reporting, and visualization support in a collaborative organization working closely with technical staff. Familiarity with environmental chemistry data generated from field investigations of water, soil, sediment, air, and biological matrices is valued. The candidate should know how to analyze system requirements and be familiar with relational databases, statistical analysis, and modern data visualization techniques using relevant and current tools. GSI provides high-quality technical and regulatory expertise to industry and government to address a broad range of environmental issues. We specialize in solving complex environmental problems by leveraging our extensive knowledge of environmental regulations, stressing accurate data collection and analysis, and applying new technologies to our clients' most difficult challenges. Responsibilities - Support environmental investigation projects by maintaining relational databases of environmental chemistry data from historical reports, laboratory test results, web sources, and third-party databases. - Build and maintain ETL (extract, transform, load) and analysis workflows in SQL, Python, and/or R to clean, transform, validate, and analyze environmental datasets. - Work with multi-disciplinary teams of engineers and scientists to support statistical and spatial analyses. - Build dashboards and visualizations, and format tables, charts, and graphs to style guidelines for technical reports and presentations. - Organize data in structures that support automation and downstream analysis. - Perform quality assurance on analytical databases to ensure data integrity, and identify and correct data gaps, errors, and relational table issues. - Support a wide variety of projects ranging from litigation support and site investigation to data mining for research and development. - Effectively communicate findings to internal and external clients. - Complete assigned tasks on schedule and within budget while meeting quality standards on deliverables. Qualifications - BS/BA or higher degree in data science, computer science, statistics, environmental science, or a related field. - 2-5 years of work experience in data management or analysis, with strong relational database skills using PostgreSQL, Microsoft SQL Server, Microsoft Access, or other database management systems. - Comfortable writing advanced SQL for data management (beyond basic create, read, update, delete), to clean, transform, and structure data in relational databases. - Familiarity with relational database design, data modeling, and normalization. - Awareness of data compilation, migration, and backup/retention considerations. - Shell scripting (Bash) and comfort working in Linux and command-line environments. - Experience using Python and/or R (Tidyverse, Shiny) for data analysis, visualization, dashboards, and web applications, including hands-on project work. - Self-motivated and eager to learn, with a drive to adopt new data and analysis techniques, AI, and emerging technologies to improve workflows. - Excellent written and verbal communication, and the ability to manage multiple tasks and meet deadlines with limited supervision. - Strong problem-solving skills and attention to detail. - Additional preferred skillsets and qualifications include: - Familiarity with chemistry data, laboratory information management systems (LIMS), data validation, and extraction of data from online sources. - Version control (Git) and reproducible, scripted analysis workflows. - Application development and deployment, including web frameworks for data tools (e.g., Django, Flask/FastAPI, Dash, Streamlit, R Shiny). Familiarity with containerization (Docker) is a plus. - Experience with embedded and analytical database engines (e.g., SQLite, DuckDB) for local analysis, prototyping, and data interchange. Job Perks - Competitive salary and benefits - Quarterly and year-end bonuses - Flexible work environment with potential for remote work - On-the-job training, mentorship, and professional development - Participation in conferences, technical presentations, and papers - Collaborative atmosphere - Base salary will vary depending on qualifications and experience. The anticipated salary range for this position is $76,000-$110,000. This range represents GSI's good-faith estimate of the base salary for the position and is provided in accordance with applicable pay transparency laws. Starting salary will be determined based on several job-related factors, including relevant experience, education, professional licensure, certifications, technical expertise, geographic location, internal equity, and overall qualifications.

• Partner with business and product teams to translate open-ended problems into clear analytical questions, measurable hypotheses and actionable recommendations. • Analyse customer journeys, funnels, engagement, and retention to identify growth opportunities. • Conduct root-cause analyses to explain changes in business metrics and recommend corrective actions. • Design and evaluate experiments with appropriate statistical and business context. • Develop dashboards, automated reporting and analytical pipelines that enable reliable decision-making. • Build or contribute to AI-enabled analytics solutions or decision-making tools. • Collaborate with data engineering teams to improve data definitions, analytical datasets, metric consistency and data quality. • Present findings to business stakeholders with storytelling and ability to zoom-out appropriately.