Top Data & Analytics Jobs

The Fraud Analyst will monitor gaming customers for fraudulent activity, analyze user behavior, and develop reporting tools while collaborating with stakeholders to enhance fraud prevention strategies.

The Business Systems Analyst provides expertise on investment accounting systems, facilitating communication between business stakeholders and technology teams, analyzing data management, and guiding complex technical solutions.

Lead analytics efforts to design and analyze experiments, perform causal and exploratory analyses, develop and monitor KPIs, build dashboards, and translate insights into recommendations for product, marketing, and business stakeholders while mentoring analysts.

The Lead, Sales Analytics & Business Intelligence will analyze data, drive business strategy, and provide insights to enhance sales growth and profitability.

Lead analytics for marketing and product decisions through causal inference, experimentation, and deep exploratory analysis. Design and evaluate A/B tests, build KPIs and dashboards, translate insights into recommendations for senior stakeholders, mentor analysts, and ensure data accuracy and integrity across platforms.

Embed with Revenue leadership to identify high-value questions, build scalable analyses, models, and visualizations, and use AI agents and LLM tooling to accelerate insight delivery. Advise data teams on models, metrics, and semantic layers; validate AI-assisted outputs; communicate recommendations to technical and executive audiences; and develop reusable tooling and documentation.

Semiconductor yield analysis internship focused on reviewing experimental data, identifying device performance shifts and process anomalies, improving measurement accuracy, and using inline data and machine learning to predict cell performance. The intern will collaborate with process integration, process engineering, and data science teams while developing root-cause analysis, process improvement, and technical communication skills.

Supports ETF market-making by configuring and validating trading logic, onboarding products, managing venue and market-data dependencies, and analyzing production trading and execution data. Builds execution-quality metrics, identifies configuration and data-quality issues, automates validation and monitoring, supports testing and deployments, and develops productivity tools. Partners with traders and technology teams to improve workflows, controls, and trading strategies.

Lead strategy, design, and implementation of enterprise employee fraud detection rules. Use advanced SAS and SQL analytics to detect anomalous activity, drive proactive monitoring, partner with senior stakeholders, ensure governance and audit readiness, and provide thought leadership on fraud detection methodologies and controls.

Design, build, and maintain optimized, highly available data pipelines and the BMG data warehouse. Lead medium-to-complex data engineering initiatives, perform solution design, code reviews, QA, data integration, and collaborate across teams. Support cloud migration and ensure compliance with data policies for reporting and analytics.

Lead design, governance, and implementation of enterprise employee fraud detection rules and proactive monitoring. Use SAS and SQL to analyze large datasets, identify emerging fraud risks, recommend rule enhancements, and partner with Risk, Compliance, Audit, and Technology to ensure effective, defensible monitoring controls and audit readiness.

Architects and leads enterprise data engineering solutions, including data warehouses, master data management, data lakes, ETL pipelines, integration services, and data processing systems. Oversees end-to-end data solutions, troubleshoots complex engineering issues, ensures global data integration standards, and mentors developers, vendors, consultants, and partners. The role also supports data scientists and engineers through efficient database, warehousing, and data access architectures.

Supports technology value realization by developing KPIs, benefit metrics, dashboards, reports, and analyses that connect technology investments to business outcomes. Partners with Product, Finance, and Technology teams to track benefits, validate data, conduct post-implementation reviews, identify variances and risks, support business cases and portfolio reporting, and improve adoption of value measurement processes.

Leads teams designing and delivering enterprise-scale batch and real-time data engineering platforms. Defines data product roadmaps, architects Kafka-based event-driven systems, builds high-throughput pipelines, establishes streaming standards and governance, and develops interoperable, AI-ready data products. Oversees organizational data policies, architecture, integrity, storage, and information management while partnering with engineering, architecture, product, and banking stakeholders.