Top Senior Analytics Jobs in Dallas, TX

Leads pricing and analytics strategy, prioritizes analytical requests, translates ambiguous business questions into recommendations, and delivers executive insights. Owns business strategy, product and pricing analytics, credit risk modeling, marketing insights, and cross-functional execution. May manage analysts, oversee projects, develop business requirements, and partner with Sales, Finance, IT, Operations, and other teams to improve profitability and performance.

Leads business analytics strategy and operational insights for a global banking services organization. Responsibilities include defining management metrics, overseeing analytics initiatives, partnering with senior stakeholders, developing executive presentations, identifying operational improvements, coordinating technology and data roadmaps, and exploring datasets through visualization and advanced analytics.

Designs and maintains data pipelines supporting monthly profitability close, automates manual finance workflows, and develops machine learning solutions for quality control, anomaly detection, and reconciliations. The role extracts and delivers financial data, prototypes LLM and agentic tools, and partners with Finance, Technology, and P&A on analytics initiatives. It also communicates technical methods and results to senior business stakeholders.

Develop global engagement strategies for Crunchyroll’s streaming platform using consumer behavior, audience segmentation, experimentation, and analytics. Analyze viewing journeys, engagement barriers, churn signals, and lifecycle interventions. Build measurement frameworks, define success metrics, evaluate A/B tests, and identify strategies that strengthen viewing habits and retention. Partner with Product, Data Science, Lifecycle, Curation, and Consumer Insights teams to translate complex behavioral data into executive-level recommendations and prioritized initiatives.

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.

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.

Support digital product analytics for an application status platform by defining measurement strategies, KPIs, analytical frameworks, dashboards, governed datasets, and anomaly alerts. Analyze platform data, identify trends and performance issues, communicate recommendations to product and technology stakeholders, and collaborate on instrumentation and pipelines. Use AI-enabled tools to accelerate validated analysis while building reusable playbooks and scalable self-service reporting capabilities.

Leads end-to-end data enablement for Supply Chain and Manufacturing domains. Partners with business and technical stakeholders to define use cases, roadmaps, data models, semantic layers, integration requirements, quality controls, and governed data products. Builds and optimizes Databricks lakehouse pipelines using SQL, Python, PySpark, and Delta Lake across complex ERP, manufacturing, procurement, inventory, and finance systems. Establishes standards for lineage, security, documentation, reliability, and production readiness.

Leads business and data analytics strategy across information management, governance, reporting, analytics delivery, and data platforms. Oversees strategic initiatives, data modernization, reporting optimization, risk controls, and cross-functional teams. Provides executive-level insights, guides architecture and technology decisions, manages priorities and capacity, and drives data-informed business outcomes. Requires substantial analytics experience in financial services, people leadership, large-scale data analysis, Agile project leadership, and strong executive communication.

Leads a food analytics team supporting sales and sourcing through market basket analyses, spend insights, reporting, automation, and analytics tools. Establishes methodologies, quality standards, and operating practices; translates complex data into actionable recommendations; partners with technology, sourcing, sales, and executive stakeholders; oversees client deliverables; improves scalability and quality assurance; and supports recruiting, coaching, and team development.

Leads wealth performance and business analytics supporting sales, investment performance, products, and strategic decisions. Develops actionable insights using market data, statistical analysis, quantitative methods, and predictive modeling. Manages analytics initiatives, leads a team, produces reports, and presents findings and recommendations to business leaders and senior management. Requires SQL and Tableau proficiency, with five or more years of reporting and analytics experience.

Owns data infrastructure, datasets, dashboards, predictive models, and AI-enabled workflows for JLL’s national industrial real estate platform. The role supports investor and occupier business development through analytics, market research, supply-chain mapping, reporting, presentations, and executive insights. Responsibilities include coordinating cross-functional teams, improving data protocols, evaluating technology platforms, automating repetitive analysis, supporting pursuits, and communicating analytical priorities to leadership.

Leads financial reporting and data analytics by developing dashboards, reporting packages, KPI insights, and data workflows. Oversees reporting governance, data quality, warehousing practices, automation, and infrastructure improvements. Manages and mentors analysts while partnering with executives, Finance, IT, and business units to translate complex data into actionable insights. Requires advanced Power BI and SQL skills, Databricks experience, and expertise in data management, reporting, and analytics.

Leads IT audit data analytics, overseeing data extraction, complex algorithms, query validation, data quality, audit reporting, and analytical support for internal audit testing. Manages, coaches, and develops Data Analyst staff; maintains knowledge of databases, audit tools, and data relationships; consults with audit leadership on analytical needs; and supports budgeting and salary evaluations.

Performs advanced analytics using predictive modeling, statistical methods, trend analysis, and diverse data sources to solve complex business problems. Builds and validates predictive models, develops business cases, creates dashboards and reports, and translates data patterns into strategic recommendations. Leads high-impact analytics projects, influences senior leadership and business decisions, develops innovative analytical approaches, and mentors others. Requires a quantitative master’s degree preferred and 7+ years of related experience.

Leads business intelligence and analytics for Verizon’s Business Markets Group. Designs measurement programs, develops advanced geospatial and financial models, evaluates sales and operational approaches, standardizes metrics, and converts complex data into strategic insights. Partners with business, technology, marketing sciences, and operational analytics teams while leading cross-functional data initiatives.

Performs complex fraud analytics and financial modeling for money movement products. Uses SAS, SQL, Excel, Tableau, and databases to evaluate fraud risk, develop mitigation strategies, improve portfolio performance, and recommend policy changes. Leads reporting, strategy requirements, testing, and rollout activities, supports biometrics enhancements, and helps implement machine learning capabilities while communicating recommendations to senior management.

Designs and governs scalable Azure data platforms, lakehouse architectures, data models, ingestion pipelines, semantic layers, and governance frameworks. The role bridges insurance systems with analytical consumers, supports real-time and batch processing, enables Power BI and AI/ML solutions, and leads cloud migrations and architecture reviews. Responsibilities include mentoring data engineers, implementing data quality and lineage controls, securing data, and collaborating with technical and business stakeholders.

Leads end-to-end marketing analytics for small business acquisition campaigns, including opportunity sizing, targeting, experimentation, performance reporting, profitability, and ROI measurement. Partners with Marketing, Finance, Modeling, and Data teams to guide investment decisions and improve measurement rigor. Owns stakeholder delivery, data requirements, analytic frameworks, controls, and auditability while coaching junior analysts and translating complex findings into clear recommendations for senior audiences.

Leads enterprise data analytics, reporting, business intelligence, dashboards, data quality, and data governance supporting Texas child welfare services. Oversees data strategy, advanced analysis, system integration, documentation, and actionable insights for leaders, staff, funders, and policymakers. Supervises analytics personnel, manages priorities and budgets, promotes ethical data stewardship, and ensures compliance with child welfare regulations. Requires collaboration with operational leaders and translation of complex data into service improvement and outcome-focused decisions.

Provides customized healthcare analytics and insights using procedural, supply utilization, cost, outcomes, and performance data. Conducts advanced comparative analyses, identifies improvement opportunities, translates findings into recommendations, presents results to clients and leaders, facilitates requirements meetings, ensures accurate reporting, and contributes to mentoring and best practices. Requires healthcare analytics experience, advanced Excel and SQL proficiency, and strong communication and problem-solving skills.

Designs and optimizes enterprise analytics solutions, including Power BI semantic models, dashboards, reports, data models, and transformations. Translates business requirements into technical specifications, leads visualization and data storytelling initiatives, validates data quality, and coordinates analytics projects. The role provides technical mentorship, improves analytics architecture and processes, and uses SQL, Python, automation, and AI-enabled tools to deliver scalable, reliable insights.

Designs, builds, deploys, and operates scalable data pipelines and cloud-based data architectures supporting lending analytics across Mortgage and Personal Loans. Responsibilities include data ingestion and transformation, schema design, SQL optimization, workflow orchestration, monitoring, troubleshooting, data quality, and generative AI integration. The role also establishes engineering standards and collaborates with analysts, engineers, and governance teams to deliver reliable production data systems.

Build and maintain dbt data models, migrate Alteryx workflows, and manage Dagster or Airflow pipelines in Redshift. Partner with Revenue Operations stakeholders to translate data into business insights, dashboards, and KPI visibility using Tableau. Apply AI, LLMs, and machine learning through SageMaker to support predictive use cases such as churn prediction and lead scoring.

Leads advanced analytics initiatives using diverse data sources, predictive modeling, statistics, and trend analysis to solve business problems and guide strategic decisions. Builds and validates complex models, develops dashboards and reports, creates business cases, and advises stakeholders on data-driven recommendations. The role influences executive decisions, leads significant projects with autonomy, mentors staff, and drives improvements across multiple business lines.