Top Hybrid Data Analysis Jobs

Develop global engagement strategies for Crunchyroll’s streaming platform using consumer behavior, audience segmentation, experimentation, and analytics. Analyze viewing journeys, engagement barriers, churn signals, and lifecycle interventions. Build measurement frameworks, define success metrics, evaluate A/B tests, and identify strategies that strengthen viewing habits and retention. Partner with Product, Data Science, Lifecycle, Curation, and Consumer Insights teams to translate complex behavioral data into executive-level recommendations and prioritized initiatives.

Conduct quantitative and qualitative analysis supporting global go-to-market and field services teams. Analyze retention, churn, product adoption, forecasting, territory design, and performance data; build dashboards, reports, queries, and automated data pipelines using Python and SQL. Partner with systems, operations, sales, and executive stakeholders to ensure data quality, prioritize requests, operationalize insights, and drive revenue-impacting decisions.

Develop and improve IP geolocation automation algorithms using large datasets and IP network topology. Query, extract, and transform data with SQL, R, Python, MongoDB, and BigQuery; provide insights that improve data quality; and collaborate with engineers, data scientists, and stakeholders to solve complex problems and lead data science initiatives.

The Quantitative Methodologist will design statistically rigorous studies, apply advanced analytics, interpret results, ensure quality, and communicate insights to clients.

Own high-impact revenue strategy analyses from problem framing through recommendations and decision support. Analyze marketplace performance, lead economics, monetization, retention, product adoption, and operating models using SQL, Python, financial modeling, and cross-functional data. Advise senior leaders, create executive- and board-ready materials, improve metric reliability, build reusable analytical frameworks, and influence decisions across Revenue, Product, Finance, and Operations.

The Data Scientist II will lead and execute health economic outcomes research projects, collaborate with stakeholders, and build analytical infrastructure while adhering to regulations.

Analyzes customer segments, KPIs, trends, and data quality to identify insights supporting acquisition, engagement, retention, and revenue growth. Partners with stakeholders on ad hoc analyses, develops dashboards and recurring reports, creates presentation materials, and translates findings into data-driven recommendations. The role requires customer data analysis, reporting, data visualization, and cross-functional collaboration in an e-commerce environment.

Analyze post-sales customer lifecycle data, including adoption, retention, renewals, churn, and expansion. Build Salesforce reports and dashboards, query and validate data with SQL, and create recurring analyses and visualizations using Excel, Tableau, and other BI tools. Partner with Customer Success, CS Operations, Analytics, BI, and Sales Systems teams to improve reporting, investigate trends, identify risks, and communicate actionable insights to technical and non-technical stakeholders.

Undergraduate interns will support data and analytics projects involving data pipelines, machine learning, generative AI, dashboards, reporting, data governance, process improvement, production support, and analytics solution development. Interns will collaborate cross-functionally, document data assets, validate data, and present project outcomes. The hybrid program requires approximately 40 hours weekly for ten weeks in Cary, North Carolina.

Leads revenue growth analytics across pricing, promotions, assortment, and market trends. Develops pricing models, promotional strategies, forecasts, KPIs, dashboards, and predictive analyses to improve sales and profitability. Partners with Sales, Marketing, Finance, and Category Management to provide actionable recommendations, influence strategic decisions, and support planning across retail, commercial, eCommerce, and direct-to-consumer channels.