Top Data Analyst Jobs in Leon

Analyze user behavior, product performance, experiments, and academic research data to guide product decisions. 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 reports, 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.

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.

Gather and document business and data requirements, create functional specifications and source-to-target mappings, and analyze healthcare payer datasets using SQL and Databricks. Define transformation rules with technical teams, support UAT and data validation, document data lineage and dictionaries, identify data quality issues, and facilitate communication between stakeholders and engineering teams to improve reporting and operational efficiency.

Build and maintain data models, dashboards, reports, and dbt models supporting cross-functional decision-making. Process large datasets, establish reporting sources of truth, bridge technical and business teams, and document knowledge bases and business definitions for internal AI systems. The role also involves identifying cost-saving opportunities, communicating with stakeholders, and using AI to develop solutions and fix bugs.

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.

Lead analytics strategy for global performance marketing by analyzing paid media, digital advertising, and campaign performance. Deliver executive reporting, ROI and incrementality analyses, experimentation, SEM payback modeling, and actionable recommendations for resource allocation and growth. Connect marketing activity with Salesforce sales pipeline data and collaborate with Marketing, Growth, Product, Sales, and Customer Success leaders to influence strategy and improve acquisition, engagement, and retention.

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.

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.

Owner of Growth experimentation and acquisition-to-conversion analytics: design rigorous tests (power, sample size, anytime-valid monitoring), produce readouts, and build a Python/dbt/Lightdash self-serve experimentation layer. Maintain a trusted funnel model (visitor→lead→customer) across channels, reduce reruns via instrumentation checks, and partner with CRO, Growth PMs, and performance marketing to turn analysis into measurable conversion wins.

Hybrid finance-data role owning financial data accuracy, infrastructure, and reporting. Maintain and QA Preset/Databricks outputs, build recurring revenue and margin reports, track KPIs and COGS, support budgeting, forecasting, variance analysis, and rolling forecasts to enable faster data-driven decisions.

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.

Supports the setup, approval, release, and tracking of new part numbers, bills of materials, and engineering change orders. Reviews changes for compliance with engineering and process standards, assigns tasks, coordinates cross-functional troubleshooting, escalates delays, and assists with testing new tools and processes. The role requires collaboration across business units and locations, knowledge of Oracle procedures, and familiarity with PLM and BOM change management.

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.

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.

Lead and own client-specific QA programs for generative AI data: set QA strategies, run root-cause analyses and CAPA, plan rater training and certification, maintain dashboards, manage escalations, standardize SOPs, pilot automations, coach raters, and ensure secure data handling across distributed teams.

Lead analytics for the curriculum subscription/ecommerce business and Post-Sales, partnering with stakeholders to deliver GTM, retention, and financial insights. Build and maintain data models and pipelines with SQL and dbt, automate and maintain BI dashboards (Sigma, Tableau), own weekly business review source files, and translate analyses into actionable recommendations.

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.