Top Remote Data Analyst Jobs in Austin, TX

As a Data Analyst, you will support senior analysts and business leaders with insights through SQL, dashboard building, and data analysis to influence revenue and retention decisions.

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.

Work with large-scale datasets to deliver advanced analytics, predictive models, and executive dashboards. Perform statistical analyses, prepare data pipelines, build reproducible workflows, and translate findings into strategic recommendations for clients and leadership. Collaborate across engineering, product, and strategy to improve analytics products and ATLAS platform capabilities.

Build and maintain Snowflake data warehouse and ETL/ELT pipelines, integrate data sources (NetSuite, Jira, portals), own BI layer and dashboards (HEX/Tableau/Looker), ensure data quality and governance, partner with leadership to translate operational goals into data models and insights, and support cross-functional analytics and automation.

As a Data Analyst, you will create dashboards, analyze data, and ensure data quality while working with the VP of Finance.

Lead BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

The Staff Data Analyst will enhance data usage for strategic decisions, architect scalable models, partner across teams on data solutions, and lead analytics engineering standards.

Collect, validate, and maintain market data across asset classes; perform statistical analysis and modeling; ensure data accuracy through QA; troubleshoot discrepancies; produce reports, dashboards, and recommendations; partner with stakeholders to improve data models and analytics practices.

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.

Analyze digital marketing campaigns and leverage data to inform business decisions, drive optimizations, and improve performance metrics.

The Business Intelligence Data Analyst II supports reporting, dashboards, and data-driven insights, working closely with Business Intelligence and Data Engineering teams. Responsibilities include optimizing data structures, leading data modeling, collaborating on requirements, and monitoring data feeds.

Design, deploy, and maintain scalable data pipelines and analytics solutions. Ensure data quality via governance and monitoring. Optimize APIM for data interaction and produce dashboards and visual reports for portfolio and divisions.

The Senior Product Data Analyst will lead analytics projects, providing strategic insights into SaaS product usage and customer behavior, while collaborating with various teams to drive business outcomes and improve product features.

The Data Analyst will perform data analysis, validation, and quality assessments, support MDM implementations, and collaborate with stakeholders to ensure accurate master data.

As a Data Analyst Intern, you will assist in data collection, cleaning, analysis, and visualization to support business decisions in a remote setup.

Analyze large training and telemetry datasets using SQL and Python to measure ROI and human risk, build executive dashboards in Looker/Tableau, audit data integrity, run behavioral analyses to identify high-risk cohorts, and present actionable insights to federal stakeholders while partnering with Data Engineering and Product.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

Support randomized control trials and A/B tests for Party at the Polls: maintain experimental data tables, prepare samples, analyze results (pre/post-election), prioritize sites, and produce reports and timely program performance analysis.

Audit and ensure quality of data labeling outputs, coach and onboard Data Labeling Associates, provide actionable feedback, monitor workflows, identify patterns and edge cases, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and validate data labeling outputs, provide structured feedback and hands-on training to annotators, monitor workflows and escalate issues, help apply and improve guidelines, and identify patterns in human and model outputs to maintain high-quality AI training data.

Audit and review data labeling outputs, provide actionable feedback, train and support labeling teams, monitor workflows, identify recurring issues and edge cases, participate in calibrations and stakeholder syncs, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and ensure quality of labeled data by reviewing DLA outputs, providing feedback and coaching, supporting onboarding and training, monitoring workflows, identifying recurring issues and edge cases, and contributing to guideline and process improvements in human-in-the-loop AI workflows.

Audit and improve data labeling quality in human-in-the-loop ML workflows. Coach and onboard labelers, provide actionable feedback, monitor queues, identify recurring issues, and help refine guidelines and processes.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, enforce and improve guidelines, identify recurring issues and edge cases, escalate risks, and document feedback to support human-in-the-loop AI workflows.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, apply and refine guidelines, monitor workflows and escalate issues, document findings, and support human-in-the-loop AI evaluation processes.