Top Hybrid Data Analysis Jobs

Analyze sales, marketing, and revenue operations data to uncover insights and improve go-to-market strategies. Collaborate with Sales, Data Science, Marketing, and Finance teams; build scalable reporting tools; and present strategic recommendations to executive leadership. The role requires SQL-based analysis, strong data management, proactive ownership, and interest in ecommerce marketplaces. Successful interns may be considered for full-time employment.

Serves as a strategic liaison between business divisions and technical teams, translating business needs into data and analytics solutions. Conducts data analysis, gathers requirements, supports reporting and integration initiatives, evaluates solution risks, and prioritizes data projects. The role guides solution design, data architecture, data quality, master data, cataloging, and advanced analytics efforts while presenting insights to business and technical stakeholders.

Supports recurring and ad hoc media analytics, reporting, data quality assurance, and performance insight development. The role gathers and validates data, creates client-ready narratives and presentations, collaborates with internal teams and external partners, and helps improve reporting workflows. Required skills include Excel, PowerPoint, data analysis, communication, and attention to detail; familiarity with Power BI, Tableau, Python, R, and SQL is valued.

Analyze consumer behavior, sales performance, marketing effectiveness, and eCommerce impact data. Build and disseminate Power BI dashboards, prepare actionable findings for Brand Marketing and Sales stakeholders, collaborate on cross-functional research projects, review presentation design consistency, and document processes. The role requires strong Excel, Power BI, and R skills, familiarity with syndicated sales data and eCommerce workflows, and the ability to communicate quantitative insights clearly.

Own the experimentation strategy for FanDuel’s generosity portfolio, prioritizing tests, guiding experiment design and analysis, translating insights into business decisions, and partnering with commercial, marketing, and data science teams. Lead and develop analysts, maintain statistical rigor, support experimentation tooling, and communicate recommendations to leadership. The role requires advanced experimentation methods, quantitative analysis, SQL, Python, Databricks, and strong stakeholder and people leadership skills.

Owns web and conversion analytics across the eCommerce journey. Analyzes customer behavior, funnels, campaigns, merchandising, retention, and commercial performance; builds dashboards and measurement plans; supports experimentation; validates tracking and data quality; develops forecasts and business cases; and presents actionable insights to senior leaders. Partners with cross-functional teams and mentors analysts while establishing analytics standards and best practices.

Sources, prepares, validates, and analyzes data to produce business intelligence reports, analytical datasets, automated processes, and insights. Collaborates with business and technology partners to define needs, improve reporting workflows, and communicate findings. Uses queries, data visualization, automation, and predictive analysis techniques while mentoring junior staff and supporting data governance and compliance.

The Senior Data Analyst translates commercial business needs into technical data specifications, writes complex SQL queries, extracts and validates large datasets, and automates workflows with Python. The role delivers accurate analytics and reporting, communicates findings to technical and non-technical stakeholders, supports pre-sales and RFP activities, manages competing requests, and collaborates with Operations, Strategy, and Data Engineering teams.

The Data Analyst will analyze player behavior, web and game usage data, and business processes to generate actionable insights. Responsibilities include data exploration and validation, metric development, visualization, statistical analysis, experimentation, stakeholder collaboration, and presenting recommendations that improve user experience and business growth. The role also involves translating data needs into specifications and developing skills in data cloud technologies, data science, storytelling, and AI.

Conduct end-to-end data analysis, translate ambiguous business questions into actionable recommendations, and support decision-making across company functions. Build and maintain dbt models, tests, documentation, curated tables, semantic-layer metric definitions, and BI reporting. Partner with data engineering and stakeholders to ensure data quality, governance, and self-service access for people and AI agents. Maintain dashboards and identify opportunities across multiple business verticals.