Top Analytics Jobs in Denver & Boulder, CO

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Analyzes healthcare datasets to identify trends, risks, and opportunities; develops SQL-based reports, dashboards, and data solutions using Excel and reporting tools. Supports data extraction, validation, forecasting, regulatory reporting, process improvement, and ad hoc analysis. Translates stakeholder needs into analytical requirements, presents findings, documents workflows, and collaborates cross-functionally on reporting projects.

Collects, consolidates, cleans, analyzes, and visualizes experimental data from analytical equipment, test rigs, and pilot plants. Performs statistical analysis, anomaly detection, experimental design support, equipment validation, and QA/QC activities. Presents findings to technical leadership, identifies process improvements, and helps extract actionable insights from structured and spectral data.

Owns retention analytics for a new Loyalty & Retention organization, including churn definitions, survival analysis, forecasting, experimentation, acquisition attribution, satisfaction analysis, payment recovery, and save-desk performance. The role builds reporting and predictive models from scratch, partners with BI and actuarial teams, influences cross-functional decisions, and presents retention findings and forecasts to executives.

Leads enterprise digital analytics strategy across marketing, pricing, product, and go-to-market functions. Develops AI, automation, experimentation, and advanced analytics capabilities to improve growth, conversion, retention, revenue, and margins. Oversees pricing, marketing, and product analytics while translating complex data into executive recommendations. Builds a scalable analytics organization, governance model, and operating framework, partnering with Digital, Product, Marketing, Finance, Engineering, Data Science, and regional teams.

Ten-week hybrid summer internship supporting data and analytics initiatives across banking teams. Interns will gather requirements, assemble and explore structured and unstructured data, perform analysis, identify trends, create insights and dashboards, collaborate with business partners, communicate findings, and present a capstone project. Assignments may include advanced analytics, reporting, visualization, data mining, automation, root-cause analysis, cohort analysis, and model development.

Graduate data analytics interns support data gathering, cleaning, exploration, analysis, reporting, dashboarding, visualization, and business insight initiatives. They collaborate with mentors and cross-functional teams, investigate trends, communicate findings to stakeholders, refine analytical approaches, and present project outcomes. The 10-week hybrid program is based in Columbus, Johnston, or Boston.

Analyzes web, customer, and campaign data to generate actionable digital marketing insights. Builds dashboards and presentations using Adobe Analytics, Power BI, or Tableau; evaluates site performance, media monetization, A/B tests, and web projects; supports tagging, reporting validation, and vendor implementations. The role partners with stakeholders and Agile teams, manages analytics priorities, and communicates findings to guide marketing strategy and business decisions.

Analyzes business processes and data integration needs, translates stakeholder requirements into technology solutions, and supports delivery from discovery through adoption. Responsibilities include requirements gathering, process analysis, data mapping and validation, migration, testing, stakeholder workshops, vendor coordination, implementation support, and business case development. The role also develops and maintains analytics and automation solutions using Microsoft and other business intelligence platforms.

Provides customized healthcare analytics using procedural, supply utilization, cost, outcomes, and performance data. Conducts advanced comparative analyses, identifies optimization opportunities, translates findings into recommendations, presents insights to clients and leaders, facilitates requirements meetings, ensures accurate reporting, and contributes to mentoring and best practices.

Analyzes digital and member experience data using statistical methods, experimentation, visualization, and business intelligence tools. Identifies data sources, performs exploratory analysis, documents methodologies, and translates findings into actionable recommendations for improving satisfaction, value, and service performance. Collaborates with cross-functional teams and leaders, presents insights, supports compliance, and influences business strategy through data-driven decisions.

Leads complex healthcare analytics projects using clinical, administrative, claims, and related datasets. Develops advanced SQL queries, analytical methodologies, cohorts, outcomes, and segmentation approaches; investigates data anomalies; translates client needs into analytic requirements; validates deliverables through quality assurance; and collaborates with consultants, statisticians, and subject matter experts to produce actionable insights for strategic decisions, clinical quality improvement, and real-world evidence.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

Analyzes healthcare-related data to produce reports, visualizations, and actionable insights for customers and internal stakeholders. Uses SQL and Excel to extract and supplement data, creates presentations, supports dashboard and DaaS product testing, and collaborates with product management and data engineering teams. The role also contributes to peer review, problem-solving, and ongoing development of analytical and data storytelling capabilities.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

Lead client-facing analytics implementations across Google Analytics 4, Adobe Analytics, and tag management systems. Responsibilities include designing measurement strategies, auditing digital ecosystems, managing tagging and consent platforms, developing data governance and privacy solutions, analyzing performance, aligning KPIs with business goals, presenting insights, supporting proposals, and improving internal analytics standards. Preferred experience includes server-side tagging, data clean rooms, customer data platforms, experimentation, CRM systems, and ETL tooling.

Own marketing channel performance analysis, reporting, experimentation, dashboards, and measurement frameworks. Develop incrementality, LTV, and forecasting analyses; identify data quality risks; and translate complex findings into actionable recommendations for Marketing, Growth, and Finance stakeholders. The role requires strong SQL, BI reporting, marketing measurement, experimentation, and analytical communication skills, with AI tools used to accelerate analytics workflows.

Lead advanced product analytics for a consumer product team by analyzing complex data, designing experiments, applying statistical and causal inference methods, developing metrics and reporting tools, and delivering actionable recommendations to cross-functional stakeholders and senior leadership. The role requires strong Python or R and SQL skills, product analytics experience, AI-assisted analytics proficiency, and the ability to influence product strategy.

Drive fraud strategy, policy, and analytics for money-movement fraud. Build and manage fraud rules, analyze moderately complex data sets using SQL/Python/SAS and BI tools, create predictive models and visualizations, consult stakeholders, and ensure fraud risk is identified and controlled across payment channels.

Leads complex analytics initiatives and partners with business leaders to define problems, analyze pharmacy, sales, and operational data, and develop actionable recommendations. Manages engagements across the full analytics lifecycle, from discovery through solution delivery and implementation support. Designs metrics, dashboards, frameworks, and decision-support tools while communicating insights to executive, operational, and technical audiences. The role emphasizes consultative analytics and business problem solving rather than software development or data infrastructure engineering.