Top Hybrid Data Analysis Jobs

Monitor payment, fraud, and risk metrics across iLottery and iGaming businesses. Analyze transaction performance, investigate anomalies and fraud events, identify data-quality issues, produce reporting, and recommend operational improvements and cost savings. The role uses Excel, business intelligence platforms, AI, and machine learning techniques to improve detection capabilities, maintain controls, support payment providers, and communicate findings to leadership.

Build and enhance a global corporate hierarchy framework by defining entity relationships, validating parent-subsidiary linkages, establishing governance controls, and improving data quality. The role analyzes large datasets, supports banking and regulatory use cases, collaborates with business, product, and engineering teams, and contributes to project delivery, stakeholder communication, and executive reporting.

Analyze structured and unstructured data to identify trends, patterns, business insights, and performance opportunities. Develop and maintain advanced dashboards, reports, visualizations, KPIs, forecasts, and root-cause analyses. Provide actionable recommendations to leadership and stakeholders, respond to ad hoc reporting requests, define reporting specifications, integrate and validate data, and lead small projects and initiatives with minimal supervision.

Analyze single-family mortgage portfolio risk and support development of an acquisition portfolio optimization tool. Research emerging market, regulatory, and macroeconomic risks; define model requirements with cross-functional teams; assess trends, relationships, forecasts, scenarios, and stress tests; mentor junior analysts; and present recommendations to senior management and stakeholders.

Analyzes and manages quantitative data, develops Power Automate workflows integrated with Tableau and SharePoint, and supports reporting, data quality, data modeling, and data management processes. The role includes reviewing errors, merging data sources, preparing summaries and presentation graphics, documenting corrections, and ensuring data integrity. It also requires extensive experience with web services and software testing tools, Agile testing life cycles, and secure federal client environments.

Leads qualitative and quantitative consumer research initiatives from scoping through delivery. Manages brand health trackers, analyzes sales and panel data, develops secondary research, and produces concise insights to guide strategic decisions. Partners with vendors and senior stakeholders, presents findings, manages multiple projects, and serves as a strategic thought partner across the organization.

Supports investment management data systems by improving data integrity, reporting, process automation, and operational efficiency. Processes and quality-controls portfolio data, troubleshoots systems, builds actionable reports, and assists with portfolio analysis, cash-flow projections, and financial modeling. Partners with investment, sales, client relations, and business teams while responding to data and reporting inquiries. The role also leverages AI tools to improve data access, workflow efficiency, and decision-making.

Analyzes digital, marketing, e-commerce, customer, and commercial data to identify growth opportunities and improve customer engagement. Responsibilities include evaluating campaigns and funnels, measuring attribution and ROI, building Power BI dashboards, integrating CRM and marketing data, supporting A/B testing, conducting statistical and predictive analyses, and presenting actionable recommendations to stakeholders.

Lead end-to-end analytics projects using proprietary and alternative datasets: ingest, clean, structure, analyze, and deliver clear visualizations and client-ready insights, building scalable SQL/Python/Snowflake workflows and improving data quality and models.

Serves as a bridge between business stakeholders and data engineering and analytics teams. Gathers and documents technical requirements, performs SQL-based data analysis, creates data mappings and diagrams, supports solution design, conducts QA and user acceptance testing, investigates root causes, and provides data and process analysis. Builds expertise in data warehouses, integrations, reporting, KPIs, and analytics solutions while supporting projects and ad hoc business questions.