Top Data Analyst Jobs in Rio de Janeiro

Analyze fraud trends and monitor metrics (fraud losses, false positives). Build dashboards, features, rules, and models to detect and prevent fraud. Perform human-in-the-loop reviews, collaborate with Risk Operations, Payments, Growth, and senior management, and improve operational feedback loops.

Analyze transactional and operational data to detect and reduce fraud, build and maintain fraud rules/features/models, create dashboards and reports, perform human-in-the-loop reviews, and partner with Risk Operations, Payments, Growth, and leadership to improve processes and mitigations.

Analyze fraud patterns and metrics to reduce fraud losses and false positives. Build dashboards, fraud features, rules, and models. Perform human-in-the-loop reviews, improve operational processes, and provide actionable insights to Risk Operations, Payments, Growth, and senior management.

Analyze customer behavior and product performance using large datasets; build dashboards, reports, and visualizations; develop queries and data models; perform statistical analysis, forecasting, segmentation, and A/B testing; collaborate with cross-functional teams and present actionable insights to stakeholders while improving data quality and analytics processes.

The Data Analyst will design interactive dashboards, model data, perform ETL processes, and collaborate with teams to enhance data-driven decisions using Power BI.

The Product Analyst will provide insights to empower Product Managers, analyze user data and trends, drive business recommendations, and support product initiatives and engagement tracking.

Lead analytics engagements for enterprise clients using observability and digital experience data. Manage 4–8 accounts, deliver dashboards and reports, perform ad-hoc analysis, configure Dynatrace solutions, present findings to technical and executive stakeholders, and influence product roadmap and client performance strategies.

Develop analytics solutions, collaborate on requirements, manage data quality, and create visualizations while improving reporting and platforms.

Design and maintain Power BI dashboards, build data models and DAX measures, extract/transform data with SQL and Excel, automate reports, perform data quality analysis, and present insights to finance and business stakeholders.

Build and maintain analytics data models, dashboards, and reports. Use SQL (Postgres, Trino, Iceberg) and dbt to power financial metrics. Perform deep-dive analyses using SQL and Python (Jupyter, Pandas) to answer business questions, operationalize data, and improve reporting and automation.

Perform exploratory data analysis, build and maintain Power BI dashboards, ensure data quality through cleansing and validation, collaborate with cross-functional teams to deliver data-driven insights, document methodologies and data assets, and present findings to business stakeholders.

Partner with product managers to analyze funnels, user conversations, and experiments. Deliver dashboards, bespoke analyses, A/B test support, impact sizing, and clear data-driven recommendations to guide product prioritization.

Build and maintain Power BI dashboards and KPIs, perform advanced SQL analyses, monitor data quality, collaborate with product and data engineering, support metric standardization and CI/CD for BI, and deliver ad hoc analyses to inform business decisions.

As a Product Analyst, you will empower Product Managers with insights derived from data analysis, user conversations, and behavioral trends to make informed product decisions. You'll support initiative prioritization and experimentation while creating narratives that connect data to business recommendations.

The Product Analyst will support Product Managers by analyzing data and trends, providing insights, making business recommendations, and enhancing user experiences through quantitative and qualitative analysis.

The Product Analyst will empower Product Managers through data analysis, user insights, and recommendations to inform product decisions, focusing on performance tracking and experimentation.

Work with real-world datasets to clean, transform, and analyze data using Python and spreadsheets; perform exploratory analysis, develop data models, support client reporting, and communicate insights to cross-functional teams to drive e-commerce decisions.

As a Senior Business Data Analyst, you will lead client engagements, translate business questions into analytical work, and deliver impactful data products while leveraging AI tools for efficiency.

Analyze fraud patterns, build monitoring dashboards, develop and maintain fraud features/rules and models, perform human-in-the-loop reviews, and provide data-driven insights to reduce fraud losses and improve operational efficiency.

Analyze billing and support performance, build and maintain data pipelines, apply statistical forecasting and A/B testing, collaborate cross-functionally, document analyses, and provide recommendations to reduce financial risk, disputes, churn, and operational inefficiencies.

The Senior Associate Decision Scientist role involves providing analytics support by building reports and dashboards, writing SQL, and maintaining data models while collaborating with stakeholders to derive insights.

The role involves improving data pipelines, migrating legacy systems, and ensuring data accuracy, while utilizing strong SQL and Python skills for ETL/ELT processes.

The Lead Data Analyst will document technical systems, collaborate with engineering teams, manage SME availability, and produce clear, structured documentation.

Provide data analysis and reporting as a virtual assistant: create and maintain reports, perform data entry and validation, generate visual insights, collaborate with stakeholders, track action items, and improve workflows to optimize reporting efficiency.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.