Top Data & Analytics Jobs

Collects and analyzes pit stop performance data across NASCAR, IndyCar, and sportscar programs. Responsibilities include filming and archiving practice footage, synchronizing video with timestamps, building analytical models, maintaining performance databases, and producing reports for coaches, engineers, and pit crews. The role requires advanced Excel, Microsoft Office, video analysis software, strong attention to detail, motorsports knowledge, and willingness to travel to racetracks and work weekends.

Supports data extraction, cleaning, analysis, visualization, ETL pipeline development, automated scripting, and machine learning model evaluation. The intern collaborates with data scientists and cross-functional teams, develops analytical tools, delivers actionable insights, performs ad hoc analyses, and presents project accomplishments to leadership. The three-month spring internship is intended for a currently enrolled bachelor’s student fulfilling a graduation requirement.

Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.

Conducts healthcare market research and analyzes brand, marketplace, demographic, volume, market share, payer mix, patient transfer, marketing, contact center, web, and financial data. Develops reporting, data extracts, and actionable insights for Houston Methodist leadership and marketing teams. Monitors database integrity, evaluates marketing performance, supports segmented mailings, researches healthcare market trends and competition, and presents findings to internal stakeholders.

Designs, develops, maintains, and optimizes SQL Server and Azure SQL databases, data warehouses, data marts, and ETL/ELT pipelines. Builds scalable data solutions using SSIS, Azure Data Factory, and Databricks; ensures data quality, security, governance, backup, and recovery. Partners with technical and business stakeholders on data modeling and integrations, troubleshoots production issues, tunes performance, and supports analytics tools including Power BI.

Develop and maintain cloud-native ETL pipelines and modernize the firm’s data architecture using Azure, Databricks, and Azure Data Factory. Build governed, reliable data products supporting reporting, analytics, automation, and AI use cases. Collaborate with technical and business stakeholders on data quality, security, lineage, access controls, testing, DevOps, and infrastructure-as-code practices.

Executes brand lift studies for Reddit media campaigns from setup through reporting and presentation. Responsibilities include leading client kickoffs, designing surveys, analyzing data, preparing recommendations and final reports, conducting quality checks, managing timelines, collaborating with sales and measurement teams, and improving processes. The role requires strong communication, organization, client relationship skills, digital advertising knowledge, and familiarity with experimentation and statistical methods.

Manages information governance, risk, and compliance initiatives focused on attorney and client onboarding, offboarding, client transfers, legal holds, and electronically stored information. Coordinates data identification, collection, classification, transfer, metadata accuracy, repository tracking, security controls, and workspace access. Supports attorneys and business teams, resolves policy inquiries, develops compliance procedures and educational materials, and contributes to technology workflows, integrations, analytics, and internal controls.

Analyze complex manufacturing and supply chain data to investigate critical issues, identify data quality and operational gaps, and support customer resolution. Establish data governance and contract integrity, design data quality metrics and visualizations, lead acceptance testing, and recommend system and process improvements. Partner with customers, developers, engineers, and management while prioritizing work, resolving conflicts, and improving application functionality.

Leads analytics, data architecture, outcomes measurement, health economics and outcomes research, ROI modeling, governance, and client reporting. Manages a multidisciplinary data team and partners with Engineering, Product, executives, and payer stakeholders to translate clinical and financial evidence into actionable decisions. Oversees accurate, repeatable analyses and communicates findings through dashboards, white papers, presentations, and impact briefs.