Top Entry Level Analysis Reporting Jobs in Dallas, TX

Participate in a rotational analyst development program focused on using data and technology to analyze performance trends, identify business opportunities, and support strategic decisions in the insurance industry. Build analytical, technical, business, and communication skills through training, mentorship, and rotational assignments. Use tools such as Excel, SQL, Python, R, SAS, Snowflake, Power BI, and emerging AI technologies.

Migrates customer data from legacy and competitor systems into SaaS products using SQL-based tools. Performs extraction, transformation, cleanup, validation, auditing, data mapping, and quality assurance. Develops repeatable scripts and workflows, collaborates with customers and cross-functional teams, supports testing and defect resolution, and documents migration processes. The role increasingly uses BigQuery, cloud platforms, automation, and intelligent tools while supporting global delivery across regions and time zones.

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.

Build and maintain production data pipelines and ingestion solutions using Python and AWS services. Support data lakes and lakehouse technologies including S3, Glue, Lake Formation, Apache Iceberg, Snowflake, and Databricks. Manage CI/CD pipelines with Jenkins and Bitbucket, troubleshoot pipeline issues, improve data quality, and collaborate with platform and engineering teams on shared data services.

Analyzes digital member experience, Voice of Customer, CSAT, survey, and behavioral data to identify trends, friction points, and service issues. Builds dashboards and reports using analytics tools, presents actionable recommendations to stakeholders, supports incident reviews and issue resolution, and partners with engineering, product, and reliability teams to validate fixes. Uses AI to summarize feedback, detect themes, and automate reporting while ensuring accuracy.

Analyzes borrower interactions and digital customer journeys across web and mobile channels. Defines KPIs, builds dashboards, monitors traffic and conversion, evaluates A/B tests and campaigns, validates tracking, diagnoses data discrepancies, and recommends improvements. The role also supports customer portal logic and technical issues, collaborates with development teams on tagging and data layers, maintains measurement documentation, and presents actionable findings to technical and business stakeholders.

Build and maintain SQL-based data models, transformations, pipelines, dashboards, and reports. Validate data accuracy, investigate discrepancies, monitor data quality, document provenance, and test pipelines under realistic conditions. Translate business needs into technical requirements, support ad hoc analysis, and collaborate with analysts, engineers, product partners, and stakeholders. The role includes mentorship and opportunities to develop expertise in end-to-end dataset ownership, Python automation, cloud data warehouses, and transformation tools.

Leads enterprise data governance execution and manages a team responsible for data stewardship, quality, controls, privacy, records management, and remediation. Partners with business, Technology, Risk, Compliance, Audit, and Operations stakeholders to prioritize work, manage capacity, resolve data risks, maintain lifecycle documentation, monitor quality metrics, and ensure data meets business and regulatory requirements. Drives process improvement, accountability, stakeholder communication, and people development.

Reviews annotated sensor and map data for quality, identifies recurring issues, and recommends solutions. The role prepares reports, maintains annotation policies, develops training documentation, performs data annotation, tests internal tools, reports bugs, and creates visual assets. It also collaborates with stakeholders, partners, annotators, project managers, and engineers while supporting on-road operations and evolving program priorities.

Designs, integrates, and manages scalable batch and streaming data pipelines from internal and external sources. Responsibilities include data transformation, schema and business-rule enhancements, load monitoring, troubleshooting data availability, evaluating emerging technologies, and collaborating with business, engineering, and privacy teams. The role also supports data governance, secure data handling, cloud technologies, and adoption of AI-enabled tools.