Data Analyst

• Build and maintain strong partnerships across technology, analytics, and business teams
• Prepare and deliver presentations, status updates, and recommendations to leadership and stakeholders
• Provide onboarding, training, and user support for enterprise analytics and data platforms
• Communicate platform performance, governance updates, and process changes to diverse audiences
• Promote compliance with data governance, risk management, and operational control requirements
• Monitor platform health, performance, and usage metrics to identify risks and improvement opportunities

Business Analytics Specialist

• Own Foley's enterprise data model
• Drive the medallion architecture from a product definition perspective
• Own Silver and Gold layer data definitions
• Prioritize the engineering backlog in partnership with the VP of Engineering
• Be the primary data platform partner for business stakeholders
• Own stakeholder communication
• Maintain a weekly touchpoint with the AI Value Creation Office
• Own delivery against quarterly KRs
• Own the product roadmap for Foley's intelligence self-service platform
• Own the API layer as a product
• Define and maintain the metric layer
• Partner with the data analyst and engineering to enable self-service intelligence
• Drive platform adoption and capability enablement across the organization
• Own the capabilities and paved paths backlog

Staff Product Manager, Data & Analytics

• Leading capacity planning and workforce optimization activities for the Retail Storefront Support Team
• Ensuring effective management of capacity levers, operational performance, and financial resources
• Translating business insights into actionable strategies by partnering across teams to analyze performance data, identify trends, and recommend solutions that improve customer experience, retention, productivity, and growth outcomes
• Leading discussions with key stakeholders to communicate information learned from analyses, provide input into line of business strategy development, and drive and influence business decisions
• Overseeing efforts to identify key business assumptions and hypotheses around line of business strategy
• Continuously refining hypotheses and identifying business questions to explore further
• Developing the analytical framework and blueprint to answer business questions identified in the business portfolio, product, or member experience and providing support to lower levels towards this effort
• Collaborating with key stakeholders to evaluate and uncover complex or critical strategic insights related to Profit & Loss performance including Product Strategy, Pricing, Marketing, Sales, Credit Risk, Distribution Channels, and Member Experience
• Applying expert analytical rigor to define outcome measures, improve prioritization, increase agility in decisioning, improve ability to evaluate progress towards business outcomes, and to evaluate risks to strategic goals
• Effectively influencing and driving strategic agreement utilizing subject matter expertise and interpersonal and negotiation skills
• Serving as a team lead and providing guidance and on-the-job training to team members
• Ensuring risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures

Lead Business Strategy Analyst – P&C Contact Center Workforce Analytics

• Facilitate the ideation and creation of analytical solutions for various functions
• Capture requirements and suggest improvements for analytical processes
• Collaborate extensively across cross-functional teams and the organization
• Drive the development and deployment of analytical solutions, fostering analytics and insights that yield positive business outcomes
• Ensure the development of Analytics & Insights aligns with the End-to-End (E2E) supply chain focus and business objectives
• Act as a key resource to support and drive analytics initiatives
• Ensure a high level of customer value and satisfaction through extreme ownership
• Promote the adoption and usage of analytics tools and insights
• Support training of analytic tools
• Ensure timely and efficient delivery of solutions
• Serve as a steward of your analytics by generating insights for business use cases

Principal Advanced Analytics Analyst

• Facilitate the ideation and creation of analytical solutions for various functions.
• Capture requirements and suggest improvements for analytical processes.
• Collaborate extensively across cross-functional teams and the organization.
• Drive the development and deployment of analytical solutions, fostering analytics and insights that yield positive business outcomes.
• Ensure the development of Analytics & Insights aligns with the End-to-End (E2E) supply chain focus and business objectives.
• Act as a key resource to support and drive analytics initiatives.
• Ensure a high level of customer value and satisfaction through extreme ownership.
• Promote the adoption and usage of analytics tools and insights.
• Support training of analytic tools.
• Ensure timely and efficient delivery of solutions.
• Serve as a steward of your analytics by generating insights for business use cases.

• Leverages advanced business, analytical and technical knowledge to participate or lead discussions with cross functional teams
• Applies advanced analytical techniques to solve business problems that are typically medium to large scale with significant impact to current and/or future business strategy.
• Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business objective and drive the appropriate change
• Translates recommendation into communication materials to effectively present to various levels of management.
• Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
• Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).
• Integrates/transforms disparate data sources and determines the appropriate data hygiene techniques to apply.
• Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.
• Understands and adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.
• Succinctly delivers analysis/findings in a manner that conveys understanding, influences various levels of management, garners support for recommendations, drives business decisions, and influences business strategy.
• Provides subject matter expertise in operationalizing recommendations.
• Remains informed on current data and analytics trends.

Senior Decision Science Analyst – P&C Underwriting Analytics

• Lead a high-performing team responsible for evaluating new and existing data assets for use across TransUnion products and services.
• Oversee end-to-end assessment of alternative and traditional data sources, including planning, execution, coverage analysis, quality validation, and business value determination.
• Develop and standardize scalable due diligence methodologies including data profiling, coverage analysis, gap analysis, lift analysis, and simulation testing.
• Translate complex analytical findings into actionable insights that influence product strategy, business decisions, and revenue-generating opportunities.
• Partner with Product, Data Acquisition, Solutions, and Technology teams to identify and prioritize opportunities that enhance existing products and support new offerings.
• Drive enterprise data quality initiatives by identifying improvement opportunities and implementing best practices across data management processes.
• Support data onboarding, cataloging, and analysis activities within the OneTru platform.
• Establish and maintain standards for data governance, data lineage, access controls, and lifecycle management.
• Lead cross-functional initiatives that influence data investment decisions and enterprise data strategy.
• Coach, mentor, and develop team members while fostering a culture of innovation, accountability, and continuous improvement.

Data Analysis Manager

• Support Cost Managers in maintaining accurate and consistent cost data structures across multiple active projects.
• Aggregate, clean, and analyze project cost data to support forecasting, reporting, and decision-making.
• Prepare corporate reporting materials, including dashboards, presentations, and executive summaries for senior leadership.
• Conduct benchmarking analysis by comparing cost and schedule data across projects, regions, and scopes to identify trends, variances, and key drivers.
• Assist in establishing and maintaining cost baselines and unit rate libraries for key data center construction components (e.g., MEP systems, structural, and site work).
• Collaborate with cross-functional teams to ensure data accuracy, consistency, and alignment with project and corporate standards.
• Support development of data visualization tools and dashboards to enhance transparency and usability of cost data.
• Validate and reconcile data from multiple sources, ensuring integrity and reliability of reporting outputs.
• Assist with ad hoc analysis and reporting requests from project teams and senior leadership.
• Effectively communicate insights, trends, and recommendations to both technical and non-technical stakeholders.
• Conduct all work with a high level of integrity and attention to detail, ensuring confidentiality and accuracy of sensitive financial data.

Data Analyst – DC Project Controls

• Define and execute enterprise strategies for Data, Integration, Analytics, and AI capabilities aligned with business objectives and enterprise architecture.
• Develop and maintain multi-year roadmaps that advance data modernization, analytics transformation, AI adoption, and integration capabilities.
• Identify strategic opportunities to improve business outcomes through data-driven decision making and intelligent automation.
• Partner with business and technology leaders to align investments with enterprise priorities and long-term growth objectives.
• Lead a portfolio of enterprise data, integration, analytics, and AI initiatives from concept through value realization.
• Establish prioritization frameworks, governance processes, and delivery models that maximize business value.
• Drive program execution, risk management, resource planning, and executive reporting across strategic initiatives.
• Ensure initiatives are delivered successfully while meeting business objectives, quality standards, and financial targets.
• Serve as a trusted advisor to senior business and technology leaders.
• Translate business priorities into technology and analytics strategies that drive measurable outcomes.
• Build strong partnerships across Commercial, Operations, Supply Chain, Finance, Quality, Manufacturing, and R&D organizations.
• Communicate vision, strategy, progress, and business value to executive stakeholders.
• Establish governance frameworks that ensure scalable, secure, compliant, and reusable enterprise solutions.
• Drive adherence to enterprise architecture principles, data governance standards, privacy requirements, and regulatory expectations.
• Promote consistency, standardization, and reuse across enterprise data and integration ecosystems.
• Define and monitor key performance indicators that measure business value, adoption, solution quality, and delivery effectiveness.
• Drive enterprise adoption of advanced analytics, AI, machine learning, and intelligent decision-support capabilities.
• Identify and prioritize high-value opportunities that leverage analytics and AI to improve business performance.
• Enable development of modern data products, semantic layers, self-service analytics, and conversational intelligence solutions.
• Foster innovation through emerging technologies and industry-leading practices.
• Lead and develop high-performing global teams consisting of employees, contractors, and strategic partners.
• Create a culture of accountability, innovation, collaboration, and continuous improvement.
• Mentor leaders and team members to strengthen technical, business, and leadership capabilities.
• Develop workforce strategies, succession plans, and talent pipelines to support future organizational needs.
• Establish organizational goals and objectives aligned with broader business and technology strategies.
• Champion inclusion, diversity, equity, and employee engagement across the organization.
• Support portfolio planning, budgeting, investment prioritization, and financial management activities.
• Partner with strategic vendors and technology providers to enable successful execution of business objectives.
• Drive cost optimization and value realization across technology investments and initiatives.

Senior IT Manager – Data, Integration & Advanced Analytics

• Oversee a team of analysts responsible for producing accurate, timely, and validated reports from our Complaint Handling and other quality systems.
• Support business decisions, regulatory submissions and audits, and inform strategic decisions within the Quality function.
• Lead the strategy, prioritization, and execution of Quality data initiatives that improve data quality, access, automation, self-service analytics, visualization, and insight generation across the Quality organization.
• Direct and oversee a dynamic team of advanced developers and analysts that plan and execute actions, develop tools and reports, and provide insights on Quality data.
• Establish and maintain effective working relationships with key stakeholders across the Enterprise with a focus on Quality and IT.
• Manage a growing portfolio of data and analytics assets and information technology infrastructure to ensure continuity and continuous improvement.
• Establish and maintain management mechanisms to drive team accountability, execution, effective communication, and cohesion.
• Oversee initiatives that drive continuous improvement with a focus on efficiency and automation.
• Manage vendor relationships and contracts.
• Represent and support the Quality Data Analytics function in audits and regulatory inquiries.

Quality Applications Manager – Quality Data Analytics

• Develop and execute comprehensive business intelligence strategies that translate client objectives into actionable KPI reporting, dashboards, and data visualizations for all account sites and service lines.
• Analyze performance metrics and variances to identify trends, recommend corrective actions, and deliver executive-level reporting that demonstrates value and drives operational improvements.
• Oversee account technology platforms (SAP, CMMS systems) and collaborate with technical teams to ensure data accuracy, system integration, and seamless migrations during upgrades.
• Design and build comprehensive reports and dashboards using SAP BusinessObjects, SAP Analytics Cloud, Power BI, or similar tools to provide stakeholders with actionable intelligence.
• Establish "Trusted Advisor" relationships with clients as a subject matter expert, ensuring satisfaction through proactive communication, responsive problem-solving, and strategic partnership.
• Partner with client governance structures in a collaborative approach to performance management, supporting forward-thinking strategies and best practice implementation.
• Collaborate with governance teams and data stewards to establish quality standards, monitoring procedures, and resolve critical data issues through root cause analysis.
• Drive process adherence and compliance while demonstrating agility to meet dynamic business needs, coordinating work between internal and external groups to streamline operations.
• Support development of the shared service model, ensuring consistency with vertical-wide initiatives while accommodating account-specific requirements.
• Foster team development through knowledge sharing, relationship building, and promotion of industry best practices in business intelligence and data management fields.

Program Manager, Performance & Analytics

• The Litigation Data Analyst – Mass Tort & Product Liability serves as a strategic insights partner to our premier mass tort and product liability practice.
• This position will leverage data analytics to guide litigation strategy, predict case outcomes, and optimize financial performance across complex multi-plaintiff litigation portfolios.
• Analyze historical verdict data, settlement patterns, and case characteristics to develop predictive models for case valuation and outcome probability
• Build comprehensive databases of comparable verdicts, settlements, and judicial decisions to support case strategy and client counseling
• Develop statistical models to assess likelihood of settlement versus trial outcomes based on case factors, jurisdiction, and opposing counsel profiles
• Create financial modeling frameworks to project settlement ranges, trial outcomes, and expected case values across different scenarios
• Monitor and analyze mass tort inventory performance, identifying trends in case development, settlement velocity, and financial outcomes
• Collaborate with litigation teams to understand case development challenges and translate them into analytical problems
• Structure complex litigation problems into clear analytical tasks, supporting strategic decision-making on case selection, resource allocation, and settlement timing
• Prioritize analyses based on case value, urgency, and strategic importance to the practice
• Design and build automated dashboards tracking key litigation metrics including case inventory, settlement rates, average case values, and practice profitability
• Create executive-level reports on practice performance, including revenue forecasts, cost analysis, and profit margins by case type and jurisdiction
• Streamline existing case reporting processes to ensure timely and accurate delivery of key performance indicators
• Present findings and recommendations in clear, concise manner tailored to different audiences (partners, associates, clients, experts)
• Clean, manipulate, and analyze large litigation datasets to extract trends, patterns, and actionable insights
• Use statistical and data modeling techniques to support litigation strategy and business development decisions
• Connect analytical findings to litigation strategy, financial outcomes, and client impact
• Partner with attorneys, paralegals, case managers, and finance teams to gather requirements and align on analytical objectives
• Collaborate with business development team to identify market opportunities and practice growth strategies
• Share knowledge and best practices with litigation teams to elevate analytical capabilities across the practice

Litigation Data Analyst – Mass Tort, Product Liability

• Work directly with Marketing, Sales, and CX leaders to diagnose business challenges, define analytical roadmaps, and drive growth strategies.
• Develop rigorous analyses, models, and frameworks to optimize customer acquisition, lifecycle engagement, and retention.
• Build scalable machine learning solutions (e.g., targeting, segmentation, uplift modeling, LTV prediction) that improve growth efficiency and ROI.
• Drive acquisition, retention, and monetization through data-driven experimentation and modeling.
• Translate complex data insights into clear, actionable recommendations that influence decision-making at all levels of the organization.
• Collaborate with engineering teams to productionize models and analytics pipelines with high reliability and performance.
• Familiar with state of art AI solutions in Data Science domain and mentor Jr. data scientists.
• Drive best practices in experimentation, measurement, and growth analytics across the company.

Lead Data Scientist – Property Catastrophe Modeling, Geo-Analytics

• Manages the end-to-end lifecycle of critical talent programs: performance management (goal setting, mid-year, and year-end) and employee engagement
• Analyzes and translates people and business data into actionable insights and recommendations that drive talent, performance, culture, and employee engagement strategies
• Consults with team members to execute various surveys, programs, and plans across the business to measure and enhance performance and impact
• Collaborates on driving the rollout of career frameworks, talent reviews, succession planning, and development planning
• Creates executive-level talent presentations that transform complex information into compelling narratives, using advanced PowerPoint design, visualization, and storytelling techniques to effectively communicate insights and recommendations
• Supports the broader HR team with a variety of ad hoc performance, talent management/ analytics-related projects and/or initiatives to support business growth and people-related objectives.

Manager, Talent & People Analytics

• Extract, transform, and analyze fleet‑scale manufacturing, testing, deployment, and operational data using advanced SQL (DML).
• Understand and translate manufacturing, quality, and reliability concepts into measurable, data‑driven solutions and KPIs.
• Perform statistical analysis on manufacturing test data to ensure data integrity, reliability, and readiness for automation and root‑cause analysis.
• Continuously provide feedback upstream to improve data quality, coverage, and performance.
• Identify and implement opportunities to automate manual workflows using AI and advanced analytics.
• Develop AI‑driven recommendation systems for data standards, anomaly detection, intelligent data mapping, and quality insights.
• Support the integration of AI and ML services (e.g., Vertex AI, LLMs) into analytics workflows and intelligent applications.
• Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes.
• Design, develop, and maintain interactive dashboards and reports using Looker Studio, Tableau, Power BI, or equivalent tools.
• Visualize manufacturing performance, data quality scores, operational metrics, headcount status, and organizational spending.
• Prepare executive‑level summaries and presentations that distill complex technical data into clear, actionable insights.
• Provide leadership with real‑time, decision‑ready visibility into manufacturing and operational health.
• Interact professionally with engineers, product owners, suppliers, and subject‑matter experts across manufacturing, quality, IT, and operations.
• Provide technical guidance to suppliers and engineering teams on optimal data collection, standards, and data warehousing solutions.
• Support multiple parallel initiatives by tracking progress, identifying risks, and escalating delivery impediments when needed.
• Facilitate change management through documentation, communication plans, and process training.

• Develop and continuously update internal identity theft and authentication models to mitigate fraud losses and reduce negative member experience from fraud applications, synthetic fraud, and account takeover attempts.
• Closely partner with the Strategy team, Director of Fraud Identity Analytics, Director of Fraud Model Management, and model users on model builds and priorities.
• Partner with Technology and other key collaborators to deploy a Member Protection graph technology strategy, including vendor selection, business requirements, data needs, and clear use cases spanning financial crimes.
• Deploy graph databases and graph techniques to identify criminal networks engaging in fraud, scams, disputes/claims, and AML, improving fraud detection and loss mitigation.
• Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience.
• Identify and work with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance.
• Exports insights to decision systems to enable better fraud targeting and model development efforts.
• Drives continuous innovation in modeling efforts including advanced techniques like graph neural networks.
• Develops and mentors junior staff, establishing a culture of R&D to augment the day-to-day aspects of the job.
• Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable sophisticated analytical solutions for the business.
• Leads and conducts sophisticated analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives.
• Guides the team selecting the appropriate modeling technique and/or technology with consideration for data limitations, application, and business needs.
• Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
• Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences.
• Partners with business leaders from across the organization to proactively identify business needs and propose/recommend analytical and modeling projects to generate business value.
• Works with business and analytics leaders to prioritize analytics and highly sophisticated modeling problems/research initiatives.
• Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code to ensure model development and research efforts are transparent and based on highest-quality data.
• Assists the team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
• Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed.
• Establishes and maintains standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards.
• Interacts with internal and external peers and management to maintain expertise and awareness of leading techniques.
• Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
• Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills.
• Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture.
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

Lead Graph Data Scientist – Identity Analytics

• Serve as the primary analytics partner for Marketing, supporting both Conference and Membership business lines
• Develop and maintain reporting frameworks for marketing campaign performance across channels
• Analyze marketing effectiveness and provide actionable recommendations to improve acquisition, engagement, and retention outcomes
• Measure campaign ROI and support data-driven budget allocation decisions
• Establish standardized marketing KPI definitions and reporting methodologies
• Develop and maintain marketing attribution frameworks across Conference and Membership initiatives
• Analyze acquisition channels, conversion funnels, and customer journeys to identify opportunities for optimization
• Support conference registration reporting and performance measurement
• Analyze subscriber acquisition, activation, retention, and lifetime value metrics
• Design and maintain executive dashboards that provide visibility into marketing performance and business outcomes

Senior Data Analyst, Marketing Analytics

• Perform quality audits and reviews of all data submitted by the IDT teams in Care Compass
• Complete quality validation calls to participants, providers, and home care agencies to confirm that all services requested were received
• Capture and modify any data missing by the PACE staff and communicate key updates
• Maintain accurate records of all scheduled appointments and ensure compliance with regulatory requirements
• Inspect participant’s requests submitted by IDT and ensure deliverables are received
• Provide analysis reports of data information to management and prepare recommendations for review

Data Quality Analyst

• This position leads the program development, implementation, and management to capture, maintain, and analyze data & work processes accurately and consistently for operational, customer, and regulatory requirements.
• Plays a crucial role in handling and analyzing large datasets to uncover valuable insights.
• Uses statistical methods, machine learning algorithms, and data visualization techniques to interpret complex data and translate the data findings into actionable business strategies that support data-driven decision-making.
• Assists in developing predictive models, automating data collection processes and ensuring data quality and integrity.
• Responsible for obtaining, creating, and analyzing data to monitor business performance & create/generate operational.
• Identifies performance trends and areas for improvement.
• Leads the development & implementation of technology, information systems, and strategies targeted at the maintenance/tracking of data ensuring compliance with all business, customer, and regulatory requirements.
• Liaison to other business areas regarding data quality & use for business reporting.
• Directs the formation, development, and implementation of tools specifically designed to improve the accuracy, timeliness, and integrity of data.
• Tracks & reports performance results.
• In cooperation with leadership, identifies actions to improve performance and/or performance tracking.
• Monitors associated change management within the business to prepare for, adopt, and sustain business changes.
• Oversees the development & maintenance of appropriate project tracking tools, system enhancements.
• Supports cross-functional collaboration in the development & tracking of business improvements supporting data management processes.
• Finds new opportunities in statistical analysis, predictive analytics, and transforming data into information with appropriate business context.
• Investigates complex data table structures to identify data relationships & the location of required data.
• Validates accuracy of the extraction or query results.
• Leads the development/implementation of technology addressing the gathering of data with regard to Capital improvements, equipment removal, ongoing maintenance, and operation of assets.
• Recognized as the key S.M.E. with leadership to understand business challenges & forge a partnering relationship for problem solving.
• Clarifies data requirements, manages expectations, and enhances organization's credibility, transparency, and partnership within Xcel and its vendor relationships.
• Supports an environment of continuous improvement & learning to foster skill development.

Data Performance Analyst

• Define and execute the enterprise Data, Analytics, AI, and Automation strategy
• Develop and maintain a multi-year roadmap for data modernization
• Advise executive leadership on emerging technologies, AI trends, opportunities, and risks
• Manage enterprise data platform architecture, including the Enterprise Data Warehouse, Azure Data Lake
• Establish enterprise data governance, data quality, and master data management capabilities
• Develop enterprise analytics capabilities that improve decision-making
• Drive adoption of intelligent automation and AI capabilities to improve productivity
• Build, lead, and develop a high-performing organization

Data Analyst jobs in Colorado

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Business Analytics Specialist

Staff Product Manager, Data & Analytics

Lead Business Strategy Analyst – P&C Contact Center Workforce Analytics

Principal Advanced Analytics Analyst

Principal Advanced Analytics Analyst

Senior Decision Science Analyst – P&C Underwriting Analytics

Data Analysis Manager

Data Analyst – DC Project Controls

Senior IT Manager – Data, Integration & Advanced Analytics

Quality Applications Manager – Quality Data Analytics

Program Manager, Performance & Analytics

Litigation Data Analyst – Mass Tort, Product Liability

Lead Data Scientist – Property Catastrophe Modeling, Geo-Analytics

Manager, Talent & People Analytics

Data Analyst

Lead Graph Data Scientist – Identity Analytics

Senior Data Analyst, Marketing Analytics

Data Quality Analyst

Data Performance Analyst

Senior Director, Enterprise Data, Analytics, AI & Automation