Top Data & Analytics Jobs

The Senior Quantitative Researcher will lead projects to enhance trading performance by developing real-time trading models and solutions for options trading, collaborating with traders and researchers.

Lead data extraction, cleaning, analysis, and visualization to identify audit risks and control weaknesses. Build GenAI code and automations to support audit planning, testing, and exception detection. Design dashboards, ensure data governance and privacy compliance, and provide data-driven insights to auditors and stakeholders while leading or guiding teams.

Design, build, and operate Alpaca's scalable data platform and lakehouse infrastructure. Build low-latency streaming and CDC ingestion, batch pipelines landing in Iceberg, and tooling for BI and AI consumers. Manage IaC, Kubernetes deployments, monitoring/incident response, and partner with DevOps and analytics teams to meet growing data requirements.

The ETL Developer will analyze data, create migration paths, develop standard queries, document processes, and ensure data quality. They must also support transitions and understand business needs.

As an Analyst, you will conduct analyses for Hive's offerings, support project delivery, collaborate with teams, and communicate project outcomes.

As a Quantitative Research Analyst, you will develop models, conduct complex data analysis, and work with stakeholders to optimize investment strategies.

Lead supply chain analytics by building Power BI dashboards, analyzing large datasets to identify trends and improve forecasting and operations. Partner with stakeholders to enable AI, automation, and predictive analytics, mentor analysts, promote best practices, and drive continuous improvement across planning, manufacturing, logistics, and inventory functions.

Lead the development of the enterprise data strategy, ensuring governance and quality while partnering with key business leaders to improve analytics and customer outcomes.

As a Staff Solutions Architect, you'll guide customers on architectural decisions, mentor teams, and influence product strategy for data lakehouses.

Lead the optimization of CRM data management, leveraging AI and analytics to enhance data integrity, automate workflows, and derive actionable insights.