Top Data & Analytics Jobs

The Business Analyst will gather business requirements, document processes, develop technical specifications, and troubleshoot production issues.

This role involves driving opportunity creation through market research, analyzing key prospect materials, and crafting tailored narratives to enhance business development efforts.

Maintain and evolve GMO's security master and portfolio data platforms (NeoXam DataHub, Aladdin, Eagle PACE). Analyze large datasets using Python, SQL, and Excel to identify data quality issues, define business requirements, support conversions/migrations, implement controls/automation, and collaborate with stakeholders to modernize data validation and onboarding processes.

This position involves supporting client-based data analytics and engineering projects, utilizing SQL, Python, or R, and presenting findings clearly.

As a Portfolio Analytics Specialist, you will oversee onboarding projects for hedge funds, address analytic challenges, and collaborate on improving software functionalities.

The role involves architecting intelligence infrastructure, building data pipelines, collaborating with other teams, and ensuring data accessibility and security for threat detection systems.

The Data Solutions Engineer will design and deliver data and analytics solutions, manage data pipelines, and support cloud platforms while collaborating with various teams to improve data accessibility and operational efficiency.

The Services Specialist will implement enterprise services, develop metrics, conduct process analysis, provide training, and manage SOA service assets.

The Data Entry Specialist will input and organize information about office buildings for landlords, ensuring data accuracy and optimizing property management efforts.

Own and operate the unified data platform and data lake powering fraud detection. Design, build, and run low-latency batch and streaming ingestion pipelines, ensure data quality/lineage/observability, support embedding/vector pipelines for generative AI, and manage deployment and CI/CD on Kubernetes while partnering with data science and product teams.