Top Remote Analytics Jobs in San Antonio, TX

Design and implement scalable data platforms, build ETL/ELT pipelines, integrate multiple data sources, define KPIs, create dashboards and executive reports, ensure data quality/governance, and collaborate with stakeholders to optimize BI capabilities.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Lead analytics for law firm operations by writing advanced SQL and Python/R scripts, building executive dashboards, standardizing KPIs, analyzing case lifecycle metrics, identifying bottlenecks, and delivering actionable recommendations to drive capacity planning and process improvements.

The Data & Analytics Architect will design and implement analytics solutions, support client engagements, and lead data architecture projects, requiring extensive technical and consulting skills.

Lead the Payments Insights Analytics team, utilizing data and AI/ML for strategy execution, operational excellence, and stakeholder communication.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Own reconciliation and validation of client billing across internal systems, build repeatable data-quality checks and documentation, support Client Group with reporting and dashboards, investigate discrepancies, and drive process improvements and automation to reduce billing friction.

Manage client data and analytics projects to design and implement data strategies, automation, visualizations, and predictive analytics. Translate data into actionable insights, lead cross-functional stakeholder engagement, scope and monitor budgets, and develop internal tools and templates. Apply finance/CPA knowledge where relevant and deliver client-facing presentations.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Support preconstruction analytics by gathering, preparing, and loading historical cost and economic data; producing reports and escalation analyses; monitoring estimate data quality; maintaining the Beck Cost Index and Bid Tab; learning DAX/Power Query/Power BI and supporting DESTINI Estimator functionality.

Lead analytics strategy and delivery for healthcare clients: gather reporting requirements, design and build enterprise data platforms (Databricks/lakehouse), develop and validate reports (including Epic reporting), influence decentralized data teams, and provide post-implementation support and modernization.

Lead analytics and data-product initiatives for healthcare clients: gather reporting requirements, design and develop reports/products, test and validate, provide post-implementation support, and partner with stakeholders to drive adoption and measurable value.

Lead quota modeling, territory design, and commission planning; maintain Salesforce data and dashboards; leverage Gong/Clari and AI tools to improve forecast accuracy; produce executive-ready sales performance analysis; collaborate cross-functionally and drive continuous improvement in reporting and data governance.

Lead analytics and insights for the CFO and exec team: produce executive-ready analyses, design scalable analytics infrastructure, leverage AI to accelerate workflows, partner cross-functionally to drive strategy and execution, and manage multiple high-impact initiatives.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Lead design and governance of enterprise ontologies, knowledge graph architecture, ingestion pipelines, and semantic layers. Enable semantic interoperability across data products, implement inference and reasoning, and establish standards, versioning, and data contracts to support scalable graph-driven analytics and AI augmentation.

Own product telemetry, maintain dbt models in Snowflake, support self-service reporting and NLP queries, drive product insights from user and retention data, and monitor Airbyte syncs to ensure data quality.

Lead development and delivery of operational Receivables reports, dashboards, and analytics. Improve KPI visibility, data integrity, and automation across Collections, Cash Applications, Credit, and Accounts Receivable. Build scalable BI solutions, validate multi-system data, standardize reporting governance, partner with Finance and operational stakeholders, and provide actionable insights to drive performance improvements.

Lead design and implementation of data models, write optimized SQL at scale, enable semantic layers and AI tooling, manage analytics infrastructure, build frontend data surfaces, and partner with product and engineering to structure source systems for reporting.

Hands-on business and delivery analyst who translates stakeholder needs into data integration solutions. Leads current/future-state and gap analysis, requirements, mapping, migration, testing, and delivery coordination. Partners with Operations, Finance, Compliance, and Purchasing to streamline workflows, promote data-driven decisions, and support adoption of analytics and cloud-based tools to improve operational outcomes.

Build and maintain production dbt models on Databricks as the organizations source of truth. Ensure data quality via testing, CI/CD, and documentation. Create Databricks dashboards and semantic metrics, support external reporting, and partner with engineering and analytics teams to turn business problems into durable data products. Drive AI-native workflows using tools like Cursor and Claude Code.

Embed with a single enterprise client to build and edit SQL for audience building and campaigns, design scalable data models, clean and automate pipelines, investigate data discrepancies, and improve workflows to support fast weekly delivery cycles.

Design analytical models, metric logic, and data schemas powering an AI marketing product; spec models and partner with engineering and AI teams; lead incrementality testing, power analysis, and MMM support; translate test results into budget recommendations and measurement guidance for paid media teams.

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

Lead a team to develop data strategy and insights across multiple business functions, driving analytics evolution and ensuring data quality and governance.