Top Data Analyst Jobs in Mexico City

The Commercial Data Analyst will support revenue optimization and data-driven projects, manage reporting tools, and collaborate with stakeholders to provide actionable insights based on data 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.

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.

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.

The Salesforce Data Hygiene Analyst ensures the accuracy and consistency of Salesforce data by resolving quality issues, developing processes, and providing analytics support.

Lead data analysis, BI, and visualization efforts: collect, clean, model, analyze, and visualize large datasets. Build dashboards and reports, apply statistical methods and data mining, ensure data quality/governance, collaborate cross-functionally, and mentor junior analysts while implementing best practices for analytics and reporting.

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.

Support warehouse operations by analyzing performance data, building dashboards and recurring reports, monitoring KPIs, performing ad-hoc analyses, validating data, automating reporting, forecasting labor needs, and presenting actionable recommendations to operations leadership to improve productivity and service.

Design, develop, and maintain Power BI dashboards and data models; write optimized SQL for extraction and transformation; implement data validation and quality checks; analyze large datasets for trends and anomalies; communicate findings and progress to stakeholders and participate in client engagements.

Build and maintain actuarial BI and reporting for reserving and pricing: clean and consolidate data, create dashboards, automate extracts/processes, audit data quality, collaborate with IT/Finance/Global Actuarial, and perform thorough quality checks and ad-hoc analyses.

As a Data Analyst, you will monitor payments performance, investigate issues, respond to user inquiries, and optimize operational processes in a fast-paced environment.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

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.

Manage and govern customer master data across ERP/CRM/MDM systems. Create, update, validate, deduplicate, and deactivate records; perform data quality checks and remediation; support compliance (SOX) and audits; handle service requests and SLA-driven ticket queues; generate quality reports; collaborate cross-functionally and mentor junior coordinators.

Lead a team of analysts to analyze large datasets, develop predictive models, create visualizations and reports, ensure data integrity, and provide strategic, sales-focused insights to guide business decisions.

Manage tracking plans and data governance for customer and product analytics. Build Mixpanel dashboards, translate business needs into technical requirements, validate data quality, consult stakeholders, and support data integration across data-marts and warehouses. Liaise between IT and Product, troubleshoot data issues, and continuously improve analytics platforms and documentation.

Support operational initiatives and technology projects across Direct Sales: coordinate projects, gather requirements, build solutions, automate workflows, develop reports/dashboards, validate data, troubleshoot issues, and document processes to improve efficiency and scalability.

Support warehouse operations by analyzing performance data, building dashboards and reports, automating recurring reporting, validating data, and providing actionable recommendations to improve productivity, labor utilization, inventory accuracy, and service performance. Partner with operations leadership for staffing, forecasting, and continuous improvement through statistical analysis and ad hoc investigations.

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.

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 Revenue Operations Data Analyst will analyze datasets, optimize dashboards, and develop data pipelines to support revenue operations and strategic decision-making.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Identify and mitigate risks in clinical trial data by conducting risk assessments, monitoring data quality, collaborating cross-functionally, using statistical analysis and visualization to report findings, and supporting regulatory risk documentation.

Lead evaluation of clinical trial data to identify risks and trends, oversee discrepancy analysis, and develop risk mitigation strategies. Partner with cross-functional stakeholders to ensure data governance, quality, and compliance. Provide guidance on best practices and drive improvements in data integrity across studies.