Top Remote Analytics Jobs in Denver & Boulder, CO

The Senior Manager, Risk Analytics will build and own Upstart's risk analytics program, managing Key Risk Indicators, data models, and reporting infrastructure for enterprise-wide risk monitoring and compliance. They will collaborate with risk owners and conduct data aggregation and reporting, supporting risk assessments and regulatory requirements.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

The Analyst I will own analytics workflows, drive improvements, build data models, and support business metrics while collaborating across teams.

The Analyst II will analyze data to optimize fraud strategies, develop machine learning models, and collaborate with teams to enhance product safety.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

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.

Perform quantitative analysis and model development support within an economic capital team. Clean and explore large datasets, run basic diagnostics, build visualizations, and assist in validating predictive and ML models using Python/R/SAS and spreadsheet tools. Help integrate AI-generated code and agentic tools under manager supervision.

Inovalon seeks candidates to join their Talent Community, emphasizing data-driven solutions to enhance healthcare outcomes and economics.

Develop and maintain value-based pro forma scenario and negotiation models, automate and standardize modeling, provide hands-on analytic support for IDN negotiations, collaborate with business partners on analytic solutions, and communicate results to stakeholders.

Embedded on a core business team, own analytics end-to-end: define problems, build reports and experiments, analyze data, surface insights, and drive recommendations that influence product, growth, AI/automation, or partnership decisions.

Lead payments analytics by building scalable reporting, causal inference and ML models, designing experiments, partnering with product/engineering/finance to optimize payment processing, reconciliation, and settlement, and translating results into executive recommendations to drive global payments improvements.

Develop, maintain, and improve predictive models and operational forecasts to support claims demand and capacity planning. Build Python workflows, prepare and validate data with SQL and Python, automate manual processes, create visualizations and BI solutions, and partner with stakeholders to translate business questions into analytical solutions while sharing knowledge with teammates.

This role involves conducting advanced data analysis to drive strategic decisions, defining metrics, collaborating with teams, and improving performance through insights.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

The Predictive Analytics Consultant designs and delivers analytics solutions for lending operations, focusing on predictive modeling, data transformation, and stakeholder communication.

Analyze ACH transaction data to enhance payment decisioning performance. Identify trends, evaluate data impact, and optimize risk strategies using Python and SQL in a fintech environment.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

The Data Scientist will enhance statistical models for forecasting, analyze datasets for operational planning, and communicate insights to stakeholders.

Manage people analytics, conducting data analysis to inform HR strategies, offer recommendations for improvement, and create reporting dashboards. Collaborate with HR and business leaders to align people data with business needs.

Lead the Retention Analytics team by providing insights into subscriber journeys, data analysis for retention strategies, and managing a team of analysts.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

Conduct research and literature reviews on disease prevalence, support projects, analyze data, and collaborate on methodology with experts.

The Analyst will analyze data, develop programming for data extraction, create reports, investigate trends, and monitor statistical models to enhance business decisions.

Partner with cross-functional teams to analyze large healthcare datasets, build models and dashboards, and surface insights to reduce medical waste. Scope, run, and present analyses, monitor performance metrics, and support initiatives to improve financial and utilization outcomes.