Data Scientist

• Develop and advance Machine Learning, Generative AI, and Computer Vision solutions.
• Implement RAG architectures, ingestion pipelines, and semantic search over vector databases.
• Build APIs and applications using LangChain, LangGraph, OpenAI, and AWS Bedrock.
• Evaluate GenAI solution performance using quality, latency, and cost metrics.
• Develop, train, and deploy image classification, detection, and segmentation models.
• Work on building and maintaining data pipelines and applications in AWS and Azure environments.
• Participate in technical decisions, refinements, and agile ceremonies, ensuring solution quality and scalability.

Senior Data Scientist – LLMs, GenAI, RAG

• Conduct studies and analyses to identify gaps, inconsistencies, and opportunities for improvement in customer/master data.
• Build statistical and predictive models for inference, recommendation, and data enrichment.
• Develop Golden Record models to ensure the best version of the customer record.
• Use graph techniques to identify complex relationships and opportunities in the master data, such as link detection, clustering, and relationship patterns between entities.
• Work with large volumes of structured and unstructured data.
• Apply data profiling, imputation, and enrichment techniques.
• Collaborate with business and engineering teams to continuously improve data quality.
• Support governance initiatives and MDM (Master Data Management) projects.
• Document methodologies, processes, and results clearly and accessibly.

Senior Data Scientist

• Lead the full lifecycle of data science projects, from understanding the business pain point to deploying and monitoring models in production;
• Develop and refine Machine Learning models (supervised and unsupervised) applied to recruitment, selection, retention and engagement;
• Conduct complex exploratory analyses to identify patterns and hidden opportunities in user behavior;
• Collaborate closely with Product and Engineering teams to integrate data solutions directly into the platform;
• Ensure model quality and governance, focusing on bias mitigation and explainability (XAI);
• Mentor more junior team members, promoting best practices in coding, experimentation and scientific rigor;
• Communicate technical findings clearly and strategically to stakeholders across different areas of the company.

• Develop predictive models for revenue and audience.
• Perform advertiser segmentation based on data and behavior.
• Build intelligent agents focused on business intelligence.
• Develop and evolve solutions using Generative AI to optimize processes and support decision-making.
• Collaborate with cross-functional teams to build data-driven products and solutions.

Data Scientist, Generative AI

• Identificar oportunidades de melhoria em áreas do negócio, propondo soluções baseadas em dados;
• Realizar análises de dados para apoiar diagnósticos e tomadas de decisões;
• Desenvolver e implantar soluções baseados em Machine Learning, NLP, IA Generativa, Otimização, Simulação, entre outros;
• Acompanhar e gerenciar projetos através de metodologias ágeis;
• Desenvolvimento interpessoal através de cursos, contato direto com clientes e trabalho em equipe.

Estágio em Data Science, IA Generativa

• Identify opportunities for improvement across business areas and propose data-driven solutions;
• Perform data analyses to support diagnostics and decision-making;
• Develop and deploy solutions based on Machine Learning, NLP, Generative AI, Optimization, Simulation, among others;

Internship, Data Science, Generative AI

• Create and structure data domains across treasury, finance, risk, FP&A, and accounting — defining granularity, business logic, and data ownership from scratch where needed
• Own source-to-target mapping end-to-end — extract, transform, enrich, cleanse, and map data from messy source systems into clean, reliable outputs
• Translate business needs into clear technical requirements — work directly with finance, treasury, and risk stakeholders to clarify what they actually need, and spec that clearly for technology teams or external vendors
• Navigate accounting and financial nuance — understand concepts like management fee structures (receivables vs. payables, date logic, transaction-level detail), ratings hierarchies, and cash flow categorization well enough to avoid pulling the wrong data
• Operate with minimal ramp-up — whether you've worked inside a comparable firm or come from a strong treasury/risk data background, you're expected to orient quickly and drive work forward without heavy training

Data Manager – Treasury

• Levantar, tratar e integrar bases internas e externas de dados imobiliários.
• Definir e calibrar drivers de valor: localização, liquidez, risco e perfil do ativo.
• Desenvolver modelos preditivos de precificação (Mark-to-Market) com machine learning e séries temporais.
• Validar modelos via backtesting e testes controlados, com ciclos iterativos de ajuste.
• Garantir monitoramento contínuo e atualização recorrente das estimativas.
• Apoiar decisões de crédito, gestão e comercialização com insights baseados em dados.
• Estruturar métricas e rotinas para evolução do piloto e operacionalização em escala.

Bolsista Mestre – Cientista de Dados Sênior, Precificação, Monitoramento de Ativos

• Collect, clean and integrate internal and external real estate data sources.
• Define and calibrate value drivers: location, liquidity, risk, and asset profile.
• Develop predictive pricing (Mark-to-Market) models using machine learning and time series methods.
• Validate models through backtesting and controlled tests, with iterative adjustment cycles.
• Ensure continuous monitoring and regular updating of estimates.
• Support credit, asset management, and sales decisions with data-driven insights.
• Structure metrics and routines for pilot evolution and operationalization at scale.

Master's Fellow – Senior Data Scientist, Asset Pricing and Monitoring

• Study new data sources
• Structure datasets
• Build variables based on Feature Learning
• Evaluate performance and feature adherence in scoring models
• Create new solutions for all market segments using statistical techniques

Data Scientist III

• Data analysis and structuring
• Development of new features
• Performance evaluation of features in scoring models
• Creation of new market solutions

Data Scientist II

• Responsável por desenvolver de projetos para aquisição de novos negócios, desde o estudo de massa para subsidiar as negociações iniciais até o momento do comitê de investimento, garantindo os atendimentos as normas e objetivo de gerar a melhor solução técnica, entregando um produto de qualidade e dentro dos prazos estabelecidos.
• Estudos de massa: desenvolver estudos de massa com estimativa de unidades com base na análise do terreno, a fim de apresentar os riscos, parâmetros e adensamento do terreno, contribuindo na negociação do terreno para equipe de prospecção.
• Anteprojeto: desenvolver estudos (projetos) de viabilidade para compra de terreno junto ao gestor, com base nas premissas legais, garantindo o adensamento maximo do terreno e melhor solução técnica.
• Viabilidade técnica de projeto: análise técnica dos projetos juntos aos fornecedores (projetistas de instalações), garantindo a viabilidade técnica do projeto.
• Logistica da obra: projetar a modulação e faseamento de obra com validação da área de logistica, garantido a execução de obra conforme premissas da companhia.
• Executivo: desenvolver, projetar e compatibilizar implantações e torres, como disciplina de arquitetura até a Liberação de Obra
• Pós Obra: retornar dúvidas e detalhes.

Analista de Projetos Pleno – Desenvolvimento de Produto

• Plan, execute and optimize paid media campaigns (Google Ads, Meta Ads and LinkedIn Ads);
• Manage acquisition strategies focused on generating qualified leads, pipeline and revenue;
• Set up and maintain offline conversions integrated between the CRM and media platforms;
• Develop automations using APIs, webhooks and tools such as n8n;
• Apply artificial intelligence to optimize campaigns, analyses and processes;
• Monitor KPIs such as CAC, ROAS, LTV, churn and payback;
• Collaborate with Marketing, Growth, SDR and Sales teams to improve results;
• Prepare management reports and present insights to support decision-making.

Mid-level Performance Analyst – SaaS Product

• Analyze growth, retention, and customer acquisition metrics, identifying opportunities to improve results.
• Develop hypotheses, run experiments, and monitor results to support business decision-making.
• Work on designing and tracking initiatives related to the customer journey and experience.
• Conduct financial impact analyses of initiatives through review of business metrics, P&L and income statement (DRE).
• Monitor metrics such as retention, churn, conversion, acquisition and lifetime value (LTV), proposing actions to optimize outcomes.
• Support discussions related to CRM, pricing, incentives and growth strategies.
• Prepare analyses and recommendations to support the area’s strategic decisions.
• Collaborate with cross-functional teams across the company to develop growth initiatives and improve the customer experience.

Senior Product Analyst - Customer Experience

• Build and maintain the multimedia product portfolio, developing plans aligned with the commercial strategy and focused on generating B2B revenue;
• Plan, manage and monitor product and offering launch projects, ensuring deadlines, deliverables, resources and alignment across involved teams;
• Develop commercial presentations (storytelling), including defining value propositions, pricing and product valuation;
• Keep ready-made commercial offerings up to date, such as media kits, corporate presentations and pricing tables;
• Conduct training sessions and product-portfolio presentations for sales teams;
• Work in partnership with the commercial team to support the sales process and participate in client meetings;
• Support management in monitoring the business’s financial performance through indicators, controls and spreadsheet analyses.

Product Planning Analyst – Multimedia

• Develop and manage relationships with strategic clients;
• Identify business opportunities and prepare value-added proposals;
• Work closely with technical teams to ensure solutions meet customer needs;
• Manage the sales pipeline and achieve sales targets defined by the company.

Senior Account Manager – ISP, Data Center

• You will bring statistical rigor to business decisions.
• Within the BI team, your mission is to go beyond descriptive analysis by applying statistical and machine learning models to find patterns, validate hypotheses, and generate forecasts that guide real strategies.
• Day-to-day, you will model complex problems with Python, work with large volumes of data in ClickHouse and BigQuery, and collaborate with product and operations teams to ensure the models deliver real value.
• Conduct statistical analyses to answer business questions: hypothesis testing, correlation analysis, segmentation, and predictive modeling;
• Perform exploratory data analysis (EDA) to understand the data before modeling, identifying patterns and inconsistencies;
• Write complex SQL queries in ClickHouse and BigQuery to extract and prepare data for analysis and modeling;
• Use Python for data manipulation, exploratory analyses, and model prototyping;
• Communicate results and insights clearly to business teams—translating statistics into decisions;
• Collaborate with the BI team to define metrics, data quality standards, and analytical best practices;
• Monitor models in production, tracking performance and proposing continuous improvements;

Data Scientist, Mid-level

• Analyze complex data and extract insights that generate value for the business and for customers
• Develop reports, dashboards and data visualizations to communicate results
• Identify trends, patterns and anomalies in the data to support strategic decision-making
• Collaborate with data engineering teams to ensure data quality, integrity and accessibility
• Create and document performance metrics and key indicators to monitor processes
• Support the definition of requirements and the specification of data-driven solutions
• Conduct feasibility studies and impact analyses of proposed solutions
• Communicate analytical findings clearly and objectively to different stakeholders

• Develop, train, and validate supervised and unsupervised Machine Learning models;
• Perform statistical and mathematical analyses to identify patterns, trends, and opportunities;
• Work with exploration, preprocessing, and modeling of large volumes of data;
• Build analytical pipelines and data preparation processes;
• Create predictive studies, segmentations, and recommendation models;
• Support business areas in data-driven decision making;
• Develop dashboards and executive presentations with analytical insights;
• Monitor performance and accuracy of deployed models;
• Collaborate with Data Engineering, BI, and business teams;
• Ensure best practices for documentation, governance, and model versioning.

• Explore, clean, and analyze large volumes of data (structured and unstructured) to identify patterns, anomalies, and opportunities.
• Develop, train, and validate predictive and prescriptive Machine Learning models (regression, classification, clustering, time series, etc.).
• Create rigorous statistical analyses and hypothesis tests to validate business assumptions.
• Translate complex mathematical metrics into reports and dashboards (Data Storytelling) for technical and non-technical stakeholders.
• Collaborate with data engineers to design efficient data pipelines that feed models in a scalable way.

Data Scientist jobs in Brazil

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Senior Data Scientist – LLMs, GenAI, RAG

Senior Data Scientist

Senior Data Scientist

Data Scientist, Generative AI

Estágio em Data Science, IA Generativa

Internship, Data Science, Generative AI

Data Manager – Treasury

Bolsista Mestre – Cientista de Dados Sênior, Precificação, Monitoramento de Ativos

Master's Fellow – Senior Data Scientist, Asset Pricing and Monitoring

Data Scientist III

Data Scientist II

Analista de Projetos Pleno – Desenvolvimento de Produto

Mid-level Performance Analyst – SaaS Product

Senior Product Analyst - Customer Experience

Product Planning Analyst – Multimedia

Senior Account Manager – ISP, Data Center

Data Scientist, Mid-level

Senior Data Scientist

Data Scientist

Junior Data Scientist