Top Remote Senior Level Data Analysis Jobs in CO

Lead statistical consulting and programming for clinical trials: design and finalize SAPs, develop randomization and IVRS specs, create and validate ADaM/SDTM analysis datasets, generate tables/listings/graphs, perform analyses (including interim/blinded), mentor/QA programmers, and support regulatory reporting and ad-hoc analyses.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

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 Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The role involves analyzing insurance classification frameworks, creating mapping documentation, and communicating classification rationale while working with stakeholders.

The Senior Product Analyst will lead analytics for the Growth & LTV team, focusing on account and program performance, designing experiments, and ensuring data-driven product decisions.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.

As a Staff Data Scientist, you will lead product strategy by building predictive models, optimizing matching algorithms, and guiding product innovations in a consumer tech environment.

The Principal, Volume Forecasting will lead the end-to-end forecasting process, utilizing data-driven models and AI tools to influence strategic decisions, manage stakeholder input, and analyze market impacts on demand.