Top Data Analyst Jobs in Leon

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.

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.

Own the growth experimentation program, including test design, power calculations, statistical rigor, readouts, and anytime-valid monitoring. Build a trusted acquisition-to-conversion funnel across paid, organic, and partner channels, incorporating CAC, LTV, and conversion metrics. Extend self-serve experimentation tooling in Lightdash and Python, improve instrumentation with Segment and Flagsmith, automate routine analysis, and influence Growth PM and marketing decisions through clear, statistically sound insights.

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.

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 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.

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.

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.

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.

The Data Analyst role focuses on leveraging advanced analytics to address strategic business challenges, including designing and implementing analytical solutions.

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.

Collaborates with clients to define business needs, designs data and business architectures, identifies data and AI opportunities, and translates requirements into technical specifications. Leads workshops, gap analyses, stakeholder alignment, governance improvements, and solution implementation. Develops delivery frameworks and accelerators while supporting client relationship growth and quantifying business value and ROI.

The Senior Data Analyst analyzes large datasets, develops SQL queries, utilizes Python for analytics, and collaborates on insights within GCP and BigQuery.

Analyze digital marketing campaign performance, investigate product and business issues, identify growth opportunities, and develop optimization strategies. The role requires working with enterprise datasets, analytical tools, automation, predictive analysis, segmentation, and visualization to deliver actionable insights and communicate data-driven recommendations to stakeholders and media partners.

Analyze digital marketing campaign performance, develop deep understanding of data sources and analytics tools, automate processes, identify growth opportunities, communicate insights, and deliver actionable optimization plans.

Collect, prepare, validate, and report statistical data for property and casualty insurance. Develop and maintain reports and analytic tools, support metadata and data dictionary upkeep, and coordinate with actuaries, product managers, regulatory affairs, finance, and IT to meet reporting requirements.

Build, maintain, and optimize data pipelines and ETL integrations (BigQuery, Fivetran, dbt). Design automations (n8n/Zapier/Make), ensure data quality and system reliability, document workflows, troubleshoot pipeline issues, and translate business needs into scalable systems to eliminate manual work.