Top Analytics Jobs in Dallas, TX

Leads risk analytics, reporting, and data strategy initiatives for Home Lending accounting and financial reporting. Reviews forecasting and aggregation models, reconciles data, documents processes, supports governance and audit readiness, and resolves complex issues across SQL, Power BI, SAS, and Microsoft 365 tools. Partners with stakeholders to automate reporting, improve transparency, validate results, and deliver analytical insights while mentoring staff and managing projects.

Lead analytics efforts for auto pricing loss estimation: develop, validate, and implement loss assumptions and statistical models (SAS/Python) to optimize portfolio profitability, support risk and regulatory requirements, monitor performance, and translate insights into strategic pricing recommendations across cross-functional stakeholders.

Leads executive-facing analytics for Home Lending Product Strategy, framing hypotheses, measuring impact, evaluating tradeoffs, and delivering recommendations and business cases. Coordinates analysts across matrixed teams, partners with Strategy, Product, Marketing, Finance, Originations, and Technology, conducts market and competitor research, and translates complex analysis into concise insights for senior decision-makers.

Leads global customer experience analytics strategy, developing analytical frameworks, predictive models, KPI systems, dashboards, forecasting, segmentation, retention analysis, and operational insights. Partners with CX, contact center, product, data, and business leaders to improve satisfaction, efficiency, retention, and business outcomes. Manages analytics initiatives and teams while translating complex data into executive-level recommendations and narratives.

Support operational reporting and analytics for Payments Operations by maintaining dashboards, scorecards, metrics, and scheduled reports. Perform SQL-based data validation, reconciliations, issue triage, root-cause coordination, ad hoc analysis, documentation, and control checks. Partner with Operations, Technology, and Data teams to improve reporting reliability, automate manual processes, strengthen governance, and communicate findings and risks to stakeholders.

Design and execute complex analyses evaluating property claims operations, process changes, tools, and vendor partnerships. Build reporting frameworks, synthesize multi-source data, and translate findings into actionable recommendations for senior stakeholders. Independently lead analytical projects that improve financial outcomes, claims handling, customer results, and operational efficiency.

Leads the Property Claims Loss Insights analytics team, setting analytical strategy, developing talent, guiding complex analyses, and translating findings into recommendations for executive and business audiences. The role evaluates financial and operational impacts of claims tools, vendors, and process changes; prioritizes high-value work; ensures methodological rigor; challenges assumptions; and partners with leadership to improve claims handling and financial outcomes.

Analyze credit expansion proposals, portfolio performance, loss forecasts, and reputational risk using internal, external, bureau, and deposit data. Develop strategy frameworks, identify emerging risk trends, diagnose performance anomalies, and recommend policy improvements. Extract and reconcile large datasets using SAS and SQL, communicate findings to senior stakeholders, validate peer analyses, and mentor junior team members.

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.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

Maintain and extend Snowflake and dbt marketing data models, dashboards, semantic models, KPI frameworks, and AI-agent validation processes. Investigate data quality issues, document metric definitions, assess downstream impacts of marketing technology changes, and translate stakeholder reporting needs into durable self-service data structures. The role requires collaboration across marketing, sales, IT, and finance to ensure trusted data and accurate AI-generated insights.

Support end-to-end payments analytics by analyzing financial and transaction data, identifying financial, credit, fraud, and reputational risks, developing analytical frameworks and dashboards, maintaining health checks, explaining profit and loss, monitoring strategy discrepancies, and reporting performance metrics. Collaborate with business teams and senior management to identify opportunities, develop risk strategies, remediate data gaps, and maintain audit-ready controls within regulatory guidelines and risk appetite thresholds.

Lead digital analytics efforts to define OKRs, run A/B tests, analyze digital customer behavior, and deliver actionable insights to product, tech, and design partners to improve engagement and customer satisfaction.

Analyze procurement data, develop dashboards and reports, validate complex datasets, identify savings opportunities, improve reporting infrastructure, and present strategic insights to management. Collaborate with data providers and procurement partners while recommending improvements to tools, processes, and data quality.

Lead quantitative and qualitative analyses to develop, implement, and monitor credit risk strategies across the card lifecycle. Define problems and success metrics, analyze customer and portfolio performance, design monitoring/reporting, perform root-cause investigations, and translate findings into executive-ready recommendations. Partner cross-functionally to implement policy and controls while ensuring governance and regulatory alignment.

Lead infrastructure analytics for Banking & Wealth Management, building measurement, forecasting, optimization, and control frameworks for token/GPU/core infrastructure. Partner with technology and finance stakeholders to create forecasting models, self-service dashboards, KPI scorecards, data governance, capacity planning, and executive-ready materials to inform investment and operational decisions.

Lead complex data initiatives from discovery through implementation and adoption. Define data structures, integrations, governance requirements, metrics, validation criteria, and reusable patterns across heterogeneous systems. Partner with business, product, technology, and data-governance teams to establish trusted data foundations, modernize legacy processes, support platform migrations, and enable reliable operational decisions and responsible AI capabilities.

Analyze large financial datasets to identify fraud risk trends, develop key risk indicators, build automated dashboards and recurring reports, and collaborate with stakeholders to inform and monitor fraud detection strategies while ensuring compliance and data governance.

Lead end-to-end MIS delivery including requirements, data acquisition, ELT/ETL pipeline development, validation, and dashboarding. Build automated pipelines, implement CI/CD/version control, apply advanced analytics (forecasting, anomaly detection, segmentation), enforce data quality and governance, translate insights for executives, prioritize and manage initiatives, mentor junior staff, and ensure audit-ready documentation and reproducibility.

Manages marketing technology, CRM data analytics, AI-enabled data enrichment, and data quality initiatives. Develops governance guardrails, standards, controls, and processes to maintain accurate data. Analyzes marketing and business development information to identify revenue and operational efficiency opportunities, creates recurring reports, collaborates with vendors and internal stakeholders, and implements tools that support strategic decision-making and demand generation.

Build governed Snowflake data marts and Sigma dashboards while migrating legacy SQL Server logic. Reverse-engineer stored procedures, views, and queries; translate business requirements into reliable reporting; establish standardized metrics, semantic layers, documentation, governance, and data-quality practices for sensitive healthcare claims data.

Analyzes fraud and account takeover risks using SQL, SAS, Excel, Tableau, and relational databases. Develops and maintains fraud detection rules, mitigation controls, monitoring processes, performance reports, and segmentation strategies. Investigates major fraud losses and emerging trends, identifies root causes, recommends policy improvements, and provides actionable insights to cross-functional stakeholders and senior management. The role focuses on minimizing fraud losses while reducing customer friction and improving operational performance.

Analyzes web, campaign, customer, and user behavior data to support digital marketing strategy. Builds dashboards and presentations using Adobe Analytics, Power BI, and Tableau; conducts A/B testing, usability analysis, and deep-dive case studies; validates tagging and reporting implementations; and provides actionable recommendations to stakeholders. The role also coordinates Agile analytics work, vendors, prioritization, and client-facing delivery.

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.