• Compreender as demandas de negócio e traduzir em tarefas técnicas com apoio do time; • Apoiar em operações de transformação e carga de dados (ETL/ELT); • Apoiar na modelagem de bancos de dados e criação de fontes de dados; • Analisar e interpretar dados utilizando técnicas estatísticas e aprendizagem de máquina; • Comunicar resultados das análises e modelos a partir de relatórios técnicos e ambientes de visualização; • Apoiar na construção e testes iniciais de modelos sob orientação; • Seguir boas práticas de APIs de consumo de modelos; • Participar da documentação e padronização de processos de análise; • Colaborar com squads multidisciplinares; • Apoiar na segurança e integridade dos dados utilizados e padronização de processos na esteira de MLOps; • Executar atividades correlatas.

• Develop Artificial Intelligence and Data Science solutions to support business decision-making; • Build, train, validate, and optimize Machine Learning and Deep Learning models; • Work on projects involving NLP, Generative AI, large language models (LLMs), and Retrieval-Augmented Generation (RAG) architectures; • Develop data pipelines and integrations using Python and SQL; • Design and implement statistical models applied to business problems; • Develop dashboards, visualizations, and analytical applications using visualization libraries and AI frameworks; • Contribute to the development and evolution of intelligent chatbots; • Work with AWS cloud environments for development and deployment of solutions; • Collaborate with cross-functional teams to define data-driven strategies; • Ensure the quality, scalability, and performance of delivered solutions; • Support technical presentations and communicate results to stakeholders.

Role Description We are seeking a Marketing Data Scientist to support and enhance internally built marketing ROI and analytics platform. This role focuses on analyzing marketing effectiveness, optimizing ad spend, and building scalable data science solutions using Python and statistical modeling techniques. The ideal candidate will have experience working with time series data, marketing analytics, and modern Python data science libraries, along with strong software engineering fundamentals. - Develop and maintain marketing ROI and analytics models - Analyze marketing and sales data to measure channel performance and advertising effectiveness - Partner with business stakeholders to address questions, review model outputs, and identify key business drivers behind marketing performance results - Work with Bayesian and linear models to evaluate marketing contribution and ROI - Support and improve Streamlit-based applications used for reporting and visualization - Build scalable Python-based data workflows and analytical tools - Export and manage reporting outputs using Excel and related formats - Collaborate with engineering and cross-functional teams to improve code quality and maintainability - Work within AWS environments including S3 and EC2 - Monitor applications and workflows using DataDog Engagement highlights: - Immediate contribution to a live ML application with clear ownership - Deep collaboration with domain experts and applied data teams - Opportunities to apply and grow expertise in both model development and deployment workflows - Overlap till 3pm CST needed Qualifications - Strong Python programming experience - Experience with: - Pandas - NumPy - PyTest - Streamlit - Experience working with time series data - Understanding of statistical modeling techniques including Bayesian and linear models - Knowledge of software engineering best practices - Experience with AWS services such as S3 and EC2 Requirements - Experience with Marketing Mix Modeling (MMM) - Nice to Have - Experience in marketing analytics or ad-tech environments - Nice to Have - Familiarity with ROI optimization and attribution modeling - Nice to Have - Exposure to DataDog or similar monitoring tools - Nice to Have - Spanish proficiency is a plus - Nice to Have

Role Description - Evaluate AI performance on land use classification and change detection using satellite imagery. - Analyze environmental monitoring and geospatial feature extraction from satellite and aerial imagery. - Assess AI-generated geospatial outputs for scientific accuracy and soundness. - Collaborate with AI research teams to improve model training and evaluation. - Work independently and asynchronously to enhance AI model performance in geospatial analysis. Qualifications - Advanced domain expertise in geospatial science. - Experience with remote sensing methodologies and GIS analysis. - Background at organizations like USGS, NASA, NOAA, or a defense/intelligence contractor. Company Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.