Top Senior Analytics Jobs in Dallas, TX

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Design and maintain core SMB Payments metrics and dashboards, perform deep-dive analyses to surface trends and drivers, build scalable datasets and self-service analytics, and apply LLM/AI techniques to augment analytics while ensuring secure, auditable production solutions.

Lead credit portfolio monitoring and risk analysis for a large commercial loans portfolio. Deliver dashboards, deep-dive analytics, and executive-ready insights for senior stakeholders. Own ad-hoc analyses, improve data quality and reporting products, and drive automation and analytics tooling adoption to inform portfolio management and risk decisions.

Lead marketing performance analytics to optimize digital acquisition funnels, measure channel and customer-level outcomes, build repeatable datasets and automation, define measurement standards, partner with Product and Technology, and quantify impact through test-and-learn approaches and operational improvements.

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.

Support home lending risk strategy by performing data-driven analyses, identifying trends, monitoring emerging housing and regulatory risks, and delivering clear recommendations and visualizations. Partner with Risk Policy, Product Strategy, and cross-functional teams to design risk segmentation, controls, and performance monitoring to align growth with the firms risk appetite.

Lead valuation and risk analytics for credit card portfolios, supporting quarterly FAS107 asset valuation. Maintain and deploy models, perform data reconciliation, forecasting, and documentation. Drive moderately complex analytics initiatives, collaborate with stakeholders, and mentor junior staff to deliver decision-focused insights and validated models.

Lead end-to-end architecture strategy for a multi-year core banking modernization program. Define target and transition architectures, govern design decisions, advise senior leaders, drive data/platform strategy, guide vendor/platform selection, ensure standards and consistency across domains, and influence delivery and investment decisions to realize target state.

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.

Lead development, validation, and implementation of credit scorecards, loss forecasting, and pricing models for auto lending. Drive complex analytical initiatives, monitor portfolio performance, and translate model outputs into strategic recommendations for senior leadership while ensuring regulatory compliance and collaboration with Risk, Finance, and operations.

Manage execution, testing, validation, and monitoring of pricing changes in Auto financing systems (CPE and LAZER). Act as liaison between Technology, Pricing, and Finance teams, develop requirements and test plans, run simulations, document results, support system upgrades/disaster recovery, and perform ad hoc portfolio performance and exception analysis.

Translate business needs into scalable analytical products for identity onboarding. Define success metrics, assess data readiness, build and productionize models (including generative AI), perform exploratory analysis and experimentation, create reusable analytics products, and communicate insights to technical and non-technical stakeholders to drive onboarding growth and risk-aware delivery.

Partner with analytics teams to measure and improve marketing effectiveness; build AI-enabled detection and alerting solutions; translate business questions into analytical approaches; deliver actionable recommendations; own projects end-to-end and communicate insights to technical and non-technical stakeholders.

Lead delivery and transformation of financial analytics for investment banking partners. Oversee team utilization and capacity planning, implement AI and automation (UIPath, Python, GPT/Claude) to create scalable products (profiles, pitchbooks, dashboards), partner with research and stakeholders, measure service effectiveness, and identify new analytics opportunities.

The Analytics Manager will lead analytics for the Payments and Identity lifecycle, manage a team of analysts, develop KPIs, and ensure data quality while collaborating with cross-functional teams.

Design, build, test, deploy, and support scalable data analytics, BI, and reporting solutions using Azure, SQL Server, Power BI, OLAP and ETL tools. Own end-to-end delivery in a small Agile team, perform data modeling, performance tuning, production support, and apply data governance and AI-enabled tools to improve automation and insights.

Lead a team to deliver reporting and analytics for wealth and distribution, using SQL and Tableau to produce reports, predictive models, and insights on sales, investment performance, and products. Present findings to senior management to support strategic decision-making.

Lead a team to perform analytics across wealth and distribution, prepare sales, investment, and product performance reporting, develop predictive and explanatory models, generate actionable insights for senior management, and present findings to inform strategic business decisions.

Lead and develop an analytics team supporting Service and Operations leaders. Prioritize and deliver dashboards, reporting, forecasts, and self-service solutions; ensure analytical quality, data validation, and documentation; identify automation and AI opportunities; translate data into actionable recommendations; and communicate findings to technical and leadership audiences.

Lead analytics for incentive compensation programs: define KPIs, build scalable pipelines, ensure data quality and audit-ready reporting, reduce operational risk, simplify reporting, partner with distribution/HR/compliance, and manage a team of analysts.

Deliver advanced analytics across the remarketing lifecycle to optimize proceeds, cycle time, and channel performance. Build scalable analytics solutions, dashboards, and scorecards; monitor performance and run strategic tests; translate data into insights for stakeholders; mentor junior analysts; ensure data governance and quality; partner cross-functionally to align metrics and drive decision-making.

Serve as a client-facing analytics subject matter expert: scope projects, define future-state visions, produce high-quality reports and dashboards, identify and fix data issues, drive data stewardship and process improvements, standardize and scale analytics services, mentor onboarding talent, and promote analytics through storytelling and cross-team collaboration.

Lead HR analytics for People & Culture and Capacity & Resource Management: build and maintain dashboards and reports, extract/clean large datasets, deliver talent and capacity insights, run data-driven programs, improve reporting processes, maintain documentation, and mentor team members while collaborating across functions to inform strategic workforce decisions.

Perform financial due diligence data analytics for middle-market M&A: obtain, validate, normalize, analyze transaction data (revenue, costs, inventory), produce dashboards and visualizations, identify trends/outliers, and communicate insights to deal teams and clients.

Build end-to-end conversion and funnel measurement for mid/lower funnel, create dashboards and attribution frameworks, analyze drop-offs and agent performance, generate actionable insights for operations, document methods, and automate reporting using AI tools.