Top Data & Analytics Jobs

Analyze options trading data, identify actionable patterns, prototype strategies with traders, and build scripts, dashboards, and automated workflows. The role requires strong Python, statistical and numerical reasoning, SQL or willingness to learn, and familiarity with AI tools. The analyst will investigate market questions, test hypotheses, identify anomalies and operational improvements, and communicate findings that improve trading decisions and desk performance.

Organizes and analyzes construction and distribution data, improves data quality and workflows, supports standardized data structures and reporting, and identifies opportunities to automate manual processes. The role collaborates with cross-functional teams to implement practical digital solutions, develop dashboards, improve data accessibility, and support operational decision-making.

Design and operate a large-scale AI/ML data platform spanning ingestion, lakehouse storage, cataloging, governance, vector search, dataset versioning, feature and embedding pipelines, observability, and low-latency retrieval. The role owns production reliability and performance, establishes data standards, supports reproducible model training, manages petabyte-scale storage, and mentors engineers while leading technical architecture.

Manage and enhance foreign-language databases, data standards, training records, reporting, and presentations supporting USSOCOM’s LREC programs. Responsibilities include database design, troubleshooting, security, recovery, performance monitoring, system upgrades, application interfaces, disaster recovery planning, and customer support. The role also provides technical guidance, coordinates database projects, prepares briefings for senior leadership, and supports language proficiency testing and bonus programs.

Leads enterprise data warehousing, data engineering, governance, security, and AI-enabled data initiatives. Oversees AWS Redshift and Informatica-based platforms, ETL pipelines, data models, quality, lineage, metadata, testing, and regulatory compliance. Drives architecture modernization, production issue resolution, CI/CD integration, and responsible AI governance. Partners with executives, technology, risk, compliance, product, and business teams while managing vendors, budgets, and a large data engineering team.

Validate and monitor risk signals used for transaction monitoring, fraud scoring, and rule-based alerting. Ingest, cleanse, transform, and assess data quality; maintain dashboards, scorecards, and documentation; support root-cause analysis, KPIs/KRIs, and remediation; collaborate with Compliance, Data, and Risk teams to refine detection logic and inform model/rule improvements.

Lead the end-to-end migration of quote-to-cash data from Salesforce CPQ and NetSuite into Salesforce Revenue Cloud Advanced and Oracle. Define migration architecture, design ETL pipelines, map and transform complex commercial and financial data, manage cleansing and reconciliation, optimize bulk loads, and lead distributed ETL developers. Produce migration specifications, runbooks, cutover plans, and audit-ready reconciliation reports while coordinating with Finance, Sales Operations, IT, and executive stakeholders.

Build and own production data pipelines, warehouse models, metric definitions, testing, monitoring, reconciliation, and alerting. Partner with Finance and other teams to create reliable datasets for usage, revenue, costs, margins, reporting, self-service analysis, and AI-assisted querying. Improve source data quality, investigate discrepancies, and establish a maintainable data foundation.

Own client relationships and analytics strategy across digital measurement and GEO initiatives. Architect, audit, and QA GA4 and Adobe Analytics implementations; develop measurement frameworks, dashboards, experimentation plans, and causal analyses. Present insights to executive stakeholders, manage analytics workstreams, mentor teammates, and build AI-assisted workflows, automations, and scalable systems. The role combines traditional analytics with measurement of AI-powered search visibility and customer behavior.

Leads commercial real estate research, analytics, forecasting, risk analysis, and market intelligence using diverse economic, financial, lending, and real estate data. Oversees research tools, models, databases, and quality processes; communicates findings through reports, presentations, webinars, podcasts, and client materials. Mentors team members, partners with Client Services, and standardizes analytical and reporting practices across the Research Group.