Top Remote Analytics Jobs in St. Louis, MO

Build and maintain Sekai's analytics transformation layer: design canonical datasets, define company-wide metrics, implement data quality and freshness checks, support experimentation and cohort/funnel analysis, and partner with product and engineering to improve instrumentation and analytics tooling.

The Senior Director will establish and lead the Real-World Data & Analytics group, oversee RWD strategy, engage in complex analytics projects, and build a high-performing team in the oncology domain.

Senior individual contributor who builds centralized analytics (Power BI), delivers insights for underwriting and distribution, standardizes surety marketing content, drives operational efficiency and automation, and leads cross-functional strategic initiatives to improve decision-making and execution.

Develop, enhance, and support Synchrony’s metadata management and cataloging platform (Ab Initio Metadata Hub). Collaborate with governance, engineering, and analytics stakeholders to ensure metadata quality, lineage, and discoverability; design solutions, implement platform changes, test, document runbooks, and enable cloud and AI/ML metadata use cases.

Lead Tableau data visualization strategy: design and optimize high-performance dashboards, establish governance and best practices, mentor teams, enable adoption, and partner with data teams for robust models and performance.

Lead intake, grooming, and translation of reporting and analytics requests into actionable requirements. Drive stakeholder sessions, define data logic and metrics, prioritize requests, enable scalable reporting solutions, support delivery and UAT, mentor junior analysts, and improve intake processes to reduce one-off requests and promote reusable, self-service reporting.

Lead digital measurement analytics for servicing platforms: design/validate data collection, build reporting and feature measurement, collaborate with stakeholders, mentor team members, and drive analytics roadmap and actionable insights.

Lead architecture and implementation of a large-scale analytics stack: design foundational pipelines, establish modeling/orchestration standards, integrate AI-assisted engineering tools, translate business questions into version-controlled data models, partner with stakeholders to define metrics and data contracts, migrate logic into maintainable pipelines, and optimize cloud warehouse performance for scale.

Lead the RevOps analytics function: manage an analytics team, own revenue reporting and forecasting, build measurement frameworks, enforce data governance, partner with BI/engineering, analyze funnel and retention metrics, and embed AI/automation to improve revenue predictability and GTM performance.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

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.

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

As a Data Analytics Engineer I, you'll bridge engineering and analytics, manage data pipelines, collaborate with stakeholders, and utilize modern open-source tech for data transformation and integration in structured finance.

The Director of Data Analytics will lead a team focused on data metrics, especially ARR, and oversee the execution of data initiatives across the organization.

The Senior Analytics Specialist develops processes for digital optimization and collaborates on A/B and multivariate testing through data insights.

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 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.

Lead enterprise data, analytics, and AI transformation engagements as a strategic advisor and architect. Design cloud data platforms, warehouses/lakehouses, governance, integration, and BI solutions. Oversee delivery, establish standards, mentor teams, support presales, and drive measurable business outcomes across technologies like Oracle, Snowflake, Databricks, and Microsoft Fabric.

The Commercial Insurance Analytics Consultant leads analytical initiatives for commercial insurance, evaluates trends and risks, and makes recommendations to senior leadership while mentoring less experienced analysts.

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.

The Senior Staff, Advanced Analytics will drive data strategy for the guest app, collaborating with stakeholders to improve conversion and create a multi-product experience through advanced data analysis and experimentation.

The Senior Finance Analytics Engineer designs dbt models, collaborates on metrics with finance teams, and enhances data for AI consumption while maintaining SOX compliance.

Design and maintain scalable data models and pipelines for analytics. Collaborate with teams to ensure reliable data supporting business insights.

Own and improve dbt models, ELT pipelines, and warehouse architecture (Snowflake or equivalent) to deliver reliable executive KPIs and metric governance. Build data spine for Finance/Operations, enforce data quality/testing, partner cross-functionally with Engineering, FP&A, and Accounting, and influence analytics engineering standards, tooling, and roadmap.

Design, build, and maintain dbt models, ELT pipelines, Looker explores and visualizations. Drive analytics strategy, data discoverability, observability, lineage, and security. Mentor engineers, collaborate cross-functionally, apply software engineering best practices, and integrate AI to scale data products and self-service BI.