Top Financial Services Data Engineering Jobs in New York City, NY

Develop and implement software solutions for automated trading systems, utilizing advanced statistical techniques to solve financial challenges.

As a Quantitative Research Engineer Intern, you will develop and implement automated trading software while collaborating with the Quantitative Research team to solve complex financial challenges.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

As a Senior Data Engineer, you will design, develop, and implement data solutions, utilizing cloud technologies and collaborating with teams to support technical solutions and mentor others.

The role involves leading Risk Data Science, developing credit decisioning models, and ensuring compliance with model risk management in a regulated environment, focusing on next-gen machine learning techniques and alternative data integration.

As a VP in QRMC, develop and maintain mathematical models, enhance risk analytics platforms, design algorithms, and work on product innovation in finance.

As the first Analytics Engineer at Rain, you will consolidate and model data sources, create reliable datasets, and develop metrics and dashboards for decision-making across the company.

Lead Aladdin client projects in data integration and conversion, collaborating with clients and stakeholders to deliver solutions on-time and on-budget.

The Head of Data will advance Addition Wealth's data strategy, managing a small team while being hands-on in analytics and data engineering to achieve measurable business outcomes.

As an Applied Research Engineer, you will drive the development of NLP systems, analyze data, collaborate with teams, and ensure efficient model integration.

As a Solutions Architect, you'll drive the strategy and implementation of cloud-based Data Fabric and Data Mesh, enabling decentralized data ownership and collaboration across teams.

The candidate designs, develops, and manages systematic market-making algorithms for electronic trading, conducting quantitative research and back-testing strategies to optimize performance and manage trading risks.