Top Hybrid Data Analysis Jobs

Analyze sales, customer, market, inventory, pricing, and demand data to produce reports, presentations, business reviews, and actionable recommendations. Support business planning, performance evaluation, competitive analysis, sales goal management, incentive administration, and strategy development. Collaborate with sales, revenue management, and demand planning leaders to identify growth opportunities, optimize product availability, and improve revenue, profitability, and market share.

Analyzes operational data, writes and maintains T-SQL scripts, investigates data quality and process issues, fulfills ad hoc business requests, builds Power BI datasets and visualizations, and supports data governance and ETL processes in partnership with IT and data warehouse teams.

Define product, feature, and agent metrics; design and analyze experiments; evaluate model and product changes; investigate performance anomalies; build statistical models, dashboards, and analytical tools; and translate complex analyses into actionable recommendations. Partner with Product, Engineering, and Machine Learning teams to improve instrumentation, data quality, experimentation systems, and understanding of customer impact.

Conduct media mix modeling, experimentation, incrementality analysis, forecasting, and marketing performance reporting. Build scalable analytical tools, automated workflows, Tableau dashboards, and statistical resources using SQL, Python, and BI platforms. Partner with Marketing, Data Science, Data Engineering, Finance, and Sales teams to improve measurement capabilities, operationalize data structures, and translate complex findings into actionable business recommendations. Maintain analytical standards, documentation, and quality controls.

Analyze SAP Community engagement data to identify trends, user interests, and content gaps. Build dashboards and executive reports measuring program reach and impact, support SAP Champions and Mentors workflows, and assist with community events. The role requires Python, SQL, Excel, Power BI, data modeling, and clear communication of insights to nontechnical stakeholders. This is a full-time hybrid internship lasting 6 to 12 months.

Build and operate Envoy’s marketing data platform on AWS, including dbt models, attribution systems, serverless applications, APIs, reverse ETL, event-lake integrations, lead-scoring models, and experimentation analytics. Partner with Marketing, RevOps, Data, and Finance to measure funnel performance, revenue attribution, CAC, payback, and channel ROI. Ensure data reliability through testing, CI, monitoring, and cost controls.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Lead marketing analytics initiatives, including experimentation, incrementality studies, customer segmentation, retention and lifetime value analysis, promotional ROI measurement, and marketing investment optimization. Build measurement frameworks, define customer data infrastructure requirements, develop dashboards, and translate complex analyses into actionable recommendations for Marketing, Product, Finance, and leadership.

Perform advanced GIS analysis, asset data management, mapping, and GIS application development for highway maintenance systems. Maintain and validate enterprise GIS datasets, develop web applications using ESRI technologies, support linear referencing systems, and coordinate technically with IT, system administrators, and users. The role also requires complex spatial analysis, multi-layered map development, troubleshooting, technical communication, and occasional in-state travel in a hybrid office environment.

Analyze deposit portfolio, customer, and market data to identify growth opportunities and optimize banking products. Build performance dashboards, develop statistical models and business cases, support pricing and product initiatives, and enhance data structures with Data Management. Partner cross-functionally with Finance, Marketing, Technology, Treasury, and Retail Administration while providing strategic insights to senior management.