Top Data Analyst Jobs in Mexico City

Develops and improves clinical site payment forecasting models, integrating enrollment, operational, and Medidata Payments data. Produces client-ready financial forecasts and reports, analyzes budget utilization and forecast variances, supports revenue recognition, audit compliance, and final payment reconciliations, and collaborates with Clinical Operations, Revenue Recognition, Project Analysis, and Clinical Payments teams across the study lifecycle.

Owns Growth and Experimentation analytics, including experiment design, power calculations, statistical readouts, funnel modeling, and self-serve analytics automation. Partners with CRO, Growth PMs, and marketing teams across acquisition and conversion channels. Builds trusted CAC, LTV, and conversion metrics while improving instrumentation, attribution quality, and experimentation rigor using SQL, Python, dbt, Lightdash, Segment, Flagsmith, and AI tooling.

Own the growth experimentation program across web, SMS, sales, and SEO. Design rigorous tests, evaluate power and statistical significance, maintain instrumentation, automate self-serve analytics tooling, and build a trusted acquisition-to-conversion funnel covering CAC, LTV, and conversion rates. Partner with CRO, marketing, and Growth PMs to turn analysis into measurable decisions and conversion improvements. The role requires expert SQL, Python, dbt, Lightdash, experimentation methodology, and strong stakeholder influence.

Analyzes and profiles data across Informatica MDM and Data 360, manages data quality issues, identifies trends and root causes, triages defects, supports end users and data stewards, and assists with UAT and technical implementations. The role requires strong SQL skills, data quality expertise, issue tracking experience, and collaboration with product and engineering teams.

Conducts strategic data analysis and statistical modeling on banking data to identify insights, improve data quality, and support business decisions. Develops data visualizations, trains machine learning models, defines analytical requirements, and creates project plans. Partners with business and IT teams to solve complex system issues, implement changes, provide application support, and communicate risks and recommendations. Requires Python, analytics, statistics, Microsoft proficiency, and strong communication skills.

Architects and develops analytics, reporting, business intelligence, and big data solutions. Builds and configures Tableau and MicroStrategy reports, uses SQL across multiple databases, and works with Hadoop, Spark, Scala, R, and related tools. Delivers actionable insights, automates reporting, supports an Analytics Center of Excellence, reviews technical designs, documents solutions, and collaborates with development teams and clients in an Agile environment.

Develops and maintains forecasting models for clinical site payments, integrating Medidata Payments data and supporting financial reporting. Analyzes plan-versus-actual performance, budget variances, and forecast risks; prepares client-ready reports and reconciliations. Partners with Revenue Recognition, Clinical Operations, Project Analysis, and planning teams to support audits, change orders, study closeouts, compliance, and sponsor reporting requirements.

Build and maintain scalable AWS data pipelines and ingestion frameworks for batch, streaming, and CDC workloads. Develop Spark and PySpark transformations, manage S3-based data lakes with Apache Iceberg, and use Glue, Athena, Lambda, and IAM. Collaborate cross-functionally, monitor pipeline health, resolve data quality issues, document architectures, and deliver reliable production data solutions.

Lead Product Data Analyst responsible for marketplace modeling, advanced SQL analysis, A/B testing, reporting, dashboard development, metrics governance, and dbt-powered data modeling. The role partners with product managers and stakeholders to turn analysis into business decisions, improve data self-service, document trusted metrics, and nurture a data-driven culture. It is a fully remote individual-contributor position focused on the Pro supply side of the marketplace.

Builds automated analytics and reporting solutions for FP&A by reverse-engineering Excel processes, querying and reconciling multi-system data, developing dashboards and interactive HTML reports, and exploring AI-assisted workflows. The role performs exploratory and driver-based analysis, improves data pipelines and data marts in partnership with engineering teams, monitors exceptions, translates findings for Finance leaders, and helps establish an AI repository for repeatable FP&A processes.

Build and maintain dashboards and recurring reports, clean and analyze operational and sales data, monitor KPIs, identify trends and anomalies, and provide actionable recommendations to managers and client stakeholders. Automate reporting processes, document data definitions, and support proactive decision-making for U.S. clients. The role is fully remote and requires collaboration during U.S. business hours.

Deliver strategic finance and analytics insights to executive leadership through SQL analysis, financial modeling, dashboards, automated reporting, and key metric forecasting. Partner cross-functionally to align metric definitions, investigate business trends, communicate findings, and support company-wide decisions. Use AI to automate analytical processes and help scale the team.

Analyze digital marketing campaign performance, investigate business and product issues, identify growth opportunities, and optimize marketplace outcomes. The role requires working with enterprise datasets, developing automated analytical processes, detecting abnormalities, conducting predictive and segmentation analysis, visualizing trends, and presenting actionable, data-driven recommendations to stakeholders and media partners.

Monitor and improve healthcare data file exchanges across clients, vendors, and internal systems. Analyze insurance claims, eligibility, enrollment, and EDI file mappings; troubleshoot data, file movement, and SFTP issues; coordinate EDI testing and implementations; validate data against business requirements; communicate operational status; and improve DataOps workflows, documentation, and processes.

Analyze user behavior, product performance, experiments, and academic research data to guide product decisions and health outcomes. Responsibilities include building Mixpanel dashboards, validating event tracking, querying Snowflake with SQL, developing Python analyses and automation, maintaining data pipelines, creating BI visualizations, conducting user research, performing statistical testing, preparing research manuscripts, and supporting grant-funded projects.

Own Trailhead’s content analytics, learner satisfaction measurement, and business impact analysis. Build semantic models, data pipelines, dashboards, cohort and propensity methodologies, predictive frameworks, and qualitative text-analysis workflows. Connect learner engagement, survey feedback, content performance, and Salesforce commercial outcomes. Lead Tableau and analytics platform strategy, make data agent-queryable, and communicate high-confidence insights to content, marketing, product, sales, customer success, and executive stakeholders.

Lead a multidisciplinary analytics team across product, retention, AI, chat, and operations. Own analytics roadmaps, KPI frameworks, dashboards, funnel and cohort analysis, retention strategy, conversational metrics, and operational performance measurement. Translate ambiguous business questions into actionable insights, product recommendations, experiments, and measurable outcomes. Partner with Product, Operations, Growth, AI, Customer Experience, and leadership while developing analytical talent and improving data-driven decision-making.

Monitor transactions and customer accounts for suspicious activity, investigate suspected fraud, analyze large datasets with SQL and Python, identify fraud patterns, document findings, and develop prevention rules and controls. The role also requires staying current on emerging fraud threats, using fraud detection tools, and leveraging Claude or equivalent large language models to improve productivity, research, and communication.

Lead a multidisciplinary analytics team supporting product, retention, AI, chat, and operations. Own KPI frameworks, conversion funnels, lifecycle and retention analysis, conversational analytics, dashboards, experimentation, and operational performance measurement. Translate ambiguous business problems into actionable insights, product recommendations, and measurable experiments while partnering with Product, Operations, Growth, Fintech, AI, and leadership stakeholders. Establish the analytical roadmap, develop team talent, and improve data-driven decision-making across the organization.

Analyze and clean data from databases, APIs, and spreadsheets; build dashboards and reports; apply statistical methods, predictive modeling, and A/B testing; and present insights to stakeholders. Gather business requirements, map processes, define technical specifications, support UAT, and liaise between business and technical teams. The role also supports project planning, system improvements, data migrations, workflow automation, and mentoring junior team members.

Maintain Salesforce account hierarchies, investigate duplicate records, validate parent-child relationships, perform OFAC and sanctions screening, and review account creation requests. Document changes for audit readiness, meet service-level agreements, evaluate AI-flagged findings, escalate risks, and recommend improvements to data-quality workflows and automation.

Analyzes human-generated data quality across AI programs using SQL, Python, statistical methods, and hands-on annotation review. Investigates quality issues, identifies failure patterns, measures impact, and develops recommendations. Supports quality pipelines, automated validations, rubrics, gold sets, calibration exercises, reporting, and dashboards. Collaborates with quality engineering, operations, delivery, and engineering teams to improve annotation design, training, tooling, and quality controls.

Design and maintain dashboards and reports, perform deep-dive analyses to identify trends and anomalies, ensure data integrity with engineers and data scientists, automate reporting, and translate complex datasets into clear insights for non-technical stakeholders.

Integrate and validate marketing data from multiple sources, ensure accurate campaign tracking and attribution, analyze paid media performance, support A/B testing, build scalable dashboards and pipelines, and partner with marketing and product teams to define KPIs and recommend optimizations.

Analyze business performance using SQL, Python, Excel, and BI tools; build data models and KPI tracking solutions; identify growth and efficiency opportunities; support long-term strategy with executive leadership; and communicate insights to cross-functional, nontechnical stakeholders. The role requires independent problem-solving and fluent English and Spanish communication.