Top Analytics Jobs in Denver & Boulder, CO

Manage and support analytics initiatives, mentor analysts, prioritize business-critical projects, and develop scalable data processes. Conduct data modeling and analysis, maintain data quality, automate workflows, and translate complex findings into actionable recommendations. Partner with product managers, business leaders, clients, and executives to advance data-driven decision-making while supporting compliance, reporting standards, and stakeholder needs.

Leads client-facing pharmacy benefit analytics using claims, utilization, savings, trend, and performance data. Develops dashboards, presentations, recommendations, and business-friendly insights; presents findings to clients and stakeholders. Manages complex analytics requests, improves reporting through automation and reusable frameworks, ensures quality and documentation, partners cross-functionally, and mentors peers while supporting scalable analytics standards and compliance.

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.

Build and own customer-facing analyses, dashboards, and reusable reporting for ECP Insights. Conduct customer discovery, define reporting needs, write SQL and Python or PySpark in Databricks, contribute dbt models, validate accuracy, explain methodologies, and help prioritize the product roadmap. Collaborate with product, engineering, and customer-facing teams while handling HIPAA-protected health information.

Provides strategic planning and advanced analytics support for healthcare clients through project-based engagements. Conducts market sizing, market scans, market share, competitive, and service line growth analyses; synthesizes data into actionable insights and recommendations for executive decision-making. Develops client deliverables and presentations, validates analytical outputs, manages data limitations, communicates findings, and supports team mentorship and best practices.

Serves as the technical and client-facing link between Inca Digital’s data engine and high-stakes financial and government clients. Conducts OSINT, web scraping, enhanced due diligence, blockchain and crypto investigations; analyzes large datasets; audits and synthesizes technical findings into intelligence reports; briefs executive stakeholders; and coordinates cross-functional teams to align products with client needs.

Own pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build supplier yield scores, pricing models, dashboards, predictive churn models, cohort analyses, and A/B tests. Partner with product, operations, engineering, sales, finance, and customer success leaders to translate marketplace data into revenue and retention improvements. Develop production machine-learning models and communicate insights to technical and non-technical stakeholders.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Leads advanced analytics for Airbnb’s Community Blueprint Quality team. Responsibilities include diagnosing customer experience issues, designing experiments, applying causal inference, developing metrics, using LLMs to analyze unstructured data, building dashboards and analytical artifacts, and translating complex findings into recommendations for senior leadership. The role partners cross-functionally with Product, Engineering, Data Science, Data Engineering, Operations, and Finance.

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.

Partners with product, business, content operations, and data teams to define measurement frameworks, analyze media production workflows, build prototypes and dashboards, strengthen data models, and provide data-driven insights for strategic decisions. The role focuses on measuring GenAI-enabled production improvements, operational efficiency, creative flexibility, and innovation impact while influencing stakeholders and leadership.

Lead analytical support for performance marketing by evaluating CAC, ROAS, LTV, conversion, retention, and acquisition efficiency. Conduct deep-dive analyses, experimentation, incrementality studies, and marketing measurement using SQL, Python, and visualization tools. Build scalable reporting frameworks, improve data quality, communicate insights to senior stakeholders, influence channel and budget decisions, and mentor junior analysts.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

Own client-facing analytics strategy and implementation across GA4, Adobe Analytics, tagging, measurement frameworks, dashboards, experimentation, and GEO measurement. Audit and QA analytics implementations, define KPIs, evaluate incrementality and causal relationships, present executive-ready insights, and collaborate with SEO, paid media, creative, data, engineering, and client teams. Build AI-assisted workflows, automations, scalable tools, and dashboards while mentoring teammates and managing multiple client workstreams.

Conduct quantitative research for traders by testing market hypotheses, building and maintaining documented signals, performing event studies and backtests, and validating results against leakage, survivorship bias, transaction costs, and regime dependence. Organize reproducible point-in-time datasets, communicate findings clearly, track signal performance, and use AI tools to accelerate research and coding while verifying outputs.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

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.

Lead a team of analysts delivering strategic analytics and business intelligence solutions. Establish data quality, governance, documentation, KPI, and reporting standards; oversee reconciliation and complex analyses; guide visualization and analytics practices; evaluate tools and automation opportunities; manage the team roadmap and performance metrics; and coach analysts while partnering with executives and stakeholders.

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.

The role involves analyzing complex datasets for private equity transactions, providing insights for due diligence and performance, using various analytics tools and programming languages, and ensuring strategic decisions are informed.