Top Senior Analytics Jobs in Denver & Boulder, CO

Lead payer analytics engagements that transform claims, membership, and operational data into actionable insights. Manage project planning, budgets, timelines, deliverables, and client workstreams while coaching analytics teams. Apply statistical analysis, predictive modeling, machine learning, SQL, dashboards, and data visualization to healthcare payer challenges. Validate data quality and analytic outputs, translate modernization needs into solutions, and guide compliance with healthcare data standards and payer regulations.

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.

Own the people analytics roadmap, build reliable HR data pipelines and reporting, and deliver workforce, talent, and process insights. Analyze employee lifecycle operations, measure performance, identify automation opportunities, and develop dashboards and predictive analyses for senior leaders. Partner across People, HRIS, IT, Finance, Legal, and data teams to improve data governance, privacy, operational efficiency, and employee experience. Establish analytical standards and coach People colleagues on data-driven decision-making.

Leads and manages a business analyst team supporting a data platform. Partners with clients, product managers, engineers, and stakeholders to gather requirements, write user stories, perform data gap analyses and source-to-target mapping, validate data using SQL, and support data quality, lineage, QA, Agile delivery, change management, and documentation. Requires healthcare data expertise, people leadership, strong communication, and experience translating technical information for varied audiences.

Lead marketplace analytics for Affirm’s two-sided ecosystem by optimizing monetization, supply, demand, pricing, profitability, and user experience. Build KPI dashboards, analyze marketplace and affiliate performance, conduct experiments, evaluate incentives and placement, and perform loan-level profitability analyses. Partner cross-functionally with Product, Engineering, Sales, Client Success, and Marketing to improve merchant value, consumer engagement, conversion, and sustainable GMV growth.

Leads commercial analytics and optimization across pricing, promotions, forecasting, financial modeling, and business intelligence. Develops analytical models, evaluates promotional effectiveness, monitors commercial KPIs, and creates dashboards and performance scorecards. Translates complex data into actionable recommendations for Commercial and Operations leaders, validates reporting data, and identifies revenue and profitability opportunities. Manages and develops a Reporting Analyst while partnering with cross-functional teams on continuous improvement.

Leads commercial analytics, pricing optimization, promotional effectiveness measurement, forecasting, financial modeling, dashboards, and performance reporting. Translates transaction and product data into recommendations that improve revenue and profitability. Partners with Commercial and Operations teams, validates reporting data, evaluates vendor-funded programs, and manages a Reporting Analyst.

Leads commercial analytics and optimization, including pricing strategy, elasticity analysis, forecasting, financial modeling, promotional effectiveness, dashboards, and performance reporting. Translates complex transaction and purchasing data into recommendations that improve revenue and profitability. Partners with Commercial and Operations teams, validates reporting data, and manages a Reporting Analyst. The role requires advanced Excel, SQL, business intelligence, statistical modeling, and quantitative analysis skills.

Leads analytics for a designated sub-vertical, serving as the primary analytics partner to Sales and senior clients. Translates ambiguous business questions into actionable insights, manages analytic engagements, supports partner performance, and influences campaign strategy. Uses SQL, AI tools, and compelling storytelling to deliver analysis, QBR narratives, measurement frameworks, and recommendations. Represents analytics in cross-functional and external discussions while helping prioritize team capacity and evolve scalable analytic processes.

Provides technical and analytical leadership for large-scale healthcare analytics solutions. Leads claims and clinical data analysis, patient journey modeling, segmentation, cohort identification, risk adjustment, and statistical modeling using SQL, Python, Spark, and Databricks. Transforms fragmented datasets into reusable analytical assets, establishes data quality and documentation standards, and partners with consulting, product, engineering, and data science teams to operationalize scalable solutions. Mentors colleagues and manages concurrent technical workstreams from design through delivery.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

Leads pharmacy and healthcare analytics projects, develops reporting frameworks, analyzes claims and utilization data, and delivers actionable insights for clients and leadership. The role translates complex findings into recommendations, ensures data quality and compliance, collaborates cross-functionally, presents results, mentors analysts, and improves analytical standards and processes.

Analyze large and complex datasets for consumer and mortgage credit-loss forecasting. Acquire and integrate data, identify trends, apply statistical techniques, interpret forecast outcomes, assess financial impacts, and provide actionable recommendations. The role also supports model risk governance, monitors recommendation results, ensures data compliance, and communicates insights to business partners.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Analyze complex healthcare, operational, clinical, utilization, workforce, and financial datasets to generate actionable insights. Develop performance measures, benchmarks, analytical models, dashboards, and stakeholder-ready presentations. Validate data integrity, conduct custom analyses, identify performance and cost-optimization opportunities, and translate findings into strategic recommendations. Collaborate with cross-functional stakeholders and automate analytical workflows and reporting processes to support healthcare quality, operational effectiveness, financial performance, and organizational growth.

Leads advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Leads Scout’s geospatial, data analytics, enterprise GIS, data governance, automation, and AI capabilities supporting renewable energy development. Establishes strategy, architecture, standards, and scalable systems for site selection, project development, engineering, construction, and investment decisions. Builds and manages a technical team, oversees technology investments and vendors, integrates business platforms, drives digital transformation, and partners with executive and cross-functional leaders to deliver measurable business outcomes.

Analyze marketing and customer data to measure campaign impact, uncover customer insights, and improve marketing ROI. Build Tableau dashboards, write and optimize SQL queries, conduct segmentation and lifecycle analysis, validate data quality, and provide actionable recommendations. Partner with marketing, product, and analytics stakeholders to translate business needs into analytical solutions and support strategy across channels, including spend allocation, targeting, attribution, and campaign effectiveness.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.

Manage and grow Ashby’s data analytics team while remaining hands-on with analytical work. The role includes hiring and coaching analysts, improving data practices, prioritizing requests, developing specialization, maintaining analytical quality, and guiding responsible AI adoption. The manager will work across raw and modeled data, dbt models, metric definitions, dashboards, and internal data products, partnering closely with business teams in a remote, high-growth B2B SaaS environment.