Top Remote Analysis Reporting Jobs in Dallas, TX

Lead processing of survey data into cloud analysis tools, build dashboards and visualizations, train and support clients, collaborate across teams, and deliver high-quality work to meet project objectives and deadlines.

The Data Scientist will work on data analysis, visualization, and reporting, utilizing various tools to assist stakeholders' needs.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Join Kled to help build the future of human data collection and design systems that influence AI data training through a consumer application.

Support and maintain the Conservancys ArcGIS and OpenGov EAM deployments, assist field staff with data collection and training, ensure data integrity, build maps/dashboards, run queries and automations, and provide administrative and project-based support for operational asset management.

Analyze product performance metrics and user behavior to drive insights for product improvements. Collaborate with teams to develop reporting practices, A/B tests, and dashboards to inform strategy.

Design and build cloud-based data applications and pipelines to analyze clinical data, enrich and provision datasets, and support clinical/operational processes. Mentor junior engineers, drive R&D for repeatable templates, collaborate with Product/Platform/Architecture, and prioritize source control, documentation, and simple solutions using modern data, ETL, and LLM tooling.

Design, build, and maintain scalable, documented data models and the Gold data layer using dbt/Coalesce. Ensure data quality through automated tests, observability, version control, and CI/CD. Optimize SQL and warehouse performance, collaborate with Data Engineering and Analytics, and support semantic layers and BI catalogs to enable trusted, self-service insights for Product, Finance, and GTM teams.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.