Top Analytics Jobs in Dallas, TX

Summer 2027 data analytics internship supporting construction operations. Responsibilities include building Power BI dashboards and reports, analyzing project and operational data, using Python and SQL for reporting and automation, automating repetitive processes, tracking KPIs, and collaborating with project controls, operations, and IT teams.

Leads complex healthcare analytics projects using clinical, administrative, claims, and related datasets. Develops advanced SQL queries, analytical methodologies, cohorts, outcomes, and segmentation approaches; investigates data anomalies; translates client needs into analytic requirements; validates deliverables through quality assurance; and collaborates with consultants, statisticians, and subject matter experts to produce actionable insights for strategic decisions, clinical quality improvement, and real-world evidence.

Lead a centralized team delivering data analytics, reporting, automation, and governance across regulatory affairs, quality assurance, and clinical functions. Define divisional strategies, standardize metrics and data sources, scale reusable dashboards and automation solutions, and improve data integrity and operational efficiency. Partner with business, technology, quality, regulatory, and clinical stakeholders while managing portfolios, capacity, budgets, performance, and change initiatives.

Leads a centralized team delivering data analytics, reporting, automation, and governance across regulatory affairs, quality assurance, and clinical functions. Establishes data ownership, metric standards, dashboards, data lineage, automation intake, and support models. Develops divisional strategies, manages portfolios and resources, partners with business and technology stakeholders, and scales analytics and automation solutions to improve data integrity, operational efficiency, and decision-making.

Analyze single-family mortgage portfolio risk and support development of an acquisition portfolio optimization tool. Research emerging market, regulatory, and macroeconomic risks; define model requirements with cross-functional teams; assess trends, relationships, forecasts, scenarios, and stress tests; mentor junior analysts; and present recommendations to senior management and stakeholders.

Supports digital experience analytics by analyzing customer data, optimizing marketing and sales programs, improving data collection and integration, building machine learning models for personalization, enabling rapid reporting, and evaluating KPIs. The internship also involves developing data products, training teams on analytics tools, and communicating actionable recommendations to stakeholders.

Leads web analytics strategy, GA4 and GTM implementations, tagging specifications, dashboards, reporting, experimentation, and data-quality monitoring. Analyzes user behavior, conversion funnels, feature adoption, and A/B test results to provide actionable recommendations for product and business decisions. Partners with product, engineering, UX, and business stakeholders and communicates analytical findings to technical and non-technical audiences.

Leads advanced analytics and data engineering for support, web, and omnichannel activities. Builds scalable batch and streaming pipelines, curated datasets, data models, dashboards, and KPI reporting. Applies data architecture, quality monitoring, observability, performance optimization, access controls, documentation, testing, and CI/CD practices. Partners with stakeholders to translate requirements into maintainable data solutions.

Drive fraud strategy, policy, and analytics for money-movement fraud. Build and manage fraud rules, analyze moderately complex data sets using SQL/Python/SAS and BI tools, create predictive models and visualizations, consult stakeholders, and ensure fraud risk is identified and controlled across payment channels.

Build and maintain healthcare data ingestion pipelines and dbt transformation models in Snowflake. Contribute to fact and dimensional modeling, semantic-layer development, data quality troubleshooting, pipeline reliability, and governed reporting. Collaborate with engineers, analysts, and stakeholders to translate requirements into technical data structures. Use AI-assisted development tools while following testing, documentation, security, SDLC, and change-management practices.

Lead and mentor an analytics team to modernize reporting, deliver automated data solutions, and improve business decisions. Manage a high-complexity reporting portfolio, translate stakeholder needs into analytical designs, champion data quality and documentation, and implement scalable workflows and visualization to drive business impact.

Analyze and organize healthcare supply purchase and contracting data to identify gaps, validate accuracy, apply contract and benchmark information, and produce customized client reporting. Translate findings into clear, data-driven insights, support purchasing and contracting decisions, manage project schedules and data requests, and collaborate with internal and external partners while developing category and industry expertise.

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.

Leads enterprise business performance analytics by evaluating organizational, financial, and operational results. Develops dashboards, executive reporting, and strategic analyses; investigates root causes, identifies risks and opportunities, monitors strategic objectives, and translates complex healthcare data into actionable recommendations. Partners cross-functionally with Finance, Actuarial, Operations, Network Management, Healthcare Management, Underwriting, Product, and executive leadership to improve enterprise performance.

Lead analytics strategy and execution for the 7‑Eleven mobile app. Partner with Product, Engineering, Marketing, and Operations to define metrics, build dashboards, run experiments and models, quantify impact, ensure data integrity and instrumentation, and translate analysis into recommendations for senior leaders.

Analytics interns will analyze datasets, generate actionable insights, develop reports, participate in the full analytics lifecycle, support model building and presentations, and complete ad hoc projects. They may work across credit risk, loan servicing, marketing, supply chain, retail, or automotive analytics. The role requires strong analytical, problem-solving, communication, and reporting skills in a fast-paced, on-site environment.

Leads the Underwriting Data Engineering team and oversees the design, development, and productionization of scalable data and machine learning pipelines. Responsibilities include feature engineering, data preparation, model deployment, data validation, governance, monitoring, API integration, analytic data products, roadmap development, stakeholder collaboration, and team coaching.

Own the Activation Factory’s partner performance measurement, analytics infrastructure, dashboards, and executive reporting. Define partner health scores and KPIs, ensure data quality across PRM, CRM, and financial systems, build pipelines and a single source of truth, and generate strategic insights on segmentation, ROI, attribution, and program effectiveness. Translate partner feedback and performance intelligence into improvements for partner programs, sales, and operations while communicating clear recommendations to senior leadership.

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.

Leads the Data Engineering and Analytics team, managing people, strategy, intake, prioritization, data pipelines, governed reporting, and stakeholder delivery. Oversees Python, SQL, dbt, Airflow, and BigQuery data products; improves reliability, code quality, and operational processes. Guides predictive and prescriptive analytics initiatives, including forecasting, recommendation, and segmentation models, with responsible healthcare data governance. Partners with product, operations, executives, clients, and vendors while supporting accurate reports, invoices, and monthly close activities.

Leads the strategy, architecture, development, and optimization of Neighborly’s AWS data platform, data lake, and enterprise data pipelines. Partners with marketing, analytics, data science, and business teams to deliver trusted data for customer engagement, reporting, AI/ML, and GenAI. Establishes engineering standards, governance, monitoring, quality, and operational processes while leading and developing a high-performing data engineering team.

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.

Owns TrendAI’s AI-generated answer visibility measurement program, including baselines, prompt methodology, recurring reporting, citation and competitive analysis, and entity representation. Translates findings into actionable content, PR, social, and messaging recommendations, partners with cross-functional teams to implement them, and evaluates outcomes. Requires enterprise B2B technology experience, AI visibility expertise, marketing analytics, knowledge-graph familiarity, technical fluency, and people-leadership readiness.

Leads marketing analytics capabilities, including KPI frameworks, recurring reports, executive dashboards, forecasting, predictive modeling, segmentation, and data governance. Translates marketing and business data into recommendations on acquisition, retention, channel performance, ROI, LTV/CAC, and brand health. Directs analytics resources and partners with Marketing, Sales, Finance, and leadership to support data-driven planning, reporting, and strategic decision-making.

Analyze healthcare claims and eligibility data to identify payment anomalies, trends, and actionable insights. Build and maintain dashboards, conduct data audits, fulfill ad hoc analytical requests, automate recurring reporting processes, and communicate findings to technical and non-technical stakeholders. The role partners with account managers, clinical teams, and operational teams to support client conversations and improve healthcare cost-management outcomes.