On Site Data Science And Analytics Jobs
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Forward Deployed AI Engineer
Forward Deployed AI EngineerNew York, NY (On-site, Full-Time)We're partnered with a premier global investment and technology firm that is making a significant investment in AI as a core business capability. As part of that effort, they're hiring Forward Deployed AI Engineers to work directly with investment teams, clients, business leaders, and dom...
Technology Solutions Engineer
Technology Solutions EngineerNew York, NY | Hybrid (4 Days Onsite)We're partnering with a leading multi-strategy investment firm seeking a Technology Solutions Engineer to join a highly visible team supporting front-office users and business-critical technology platforms.This role sits at the intersection of production engineering, platform enginee...
Risk Platform Quant Developer
About the RoleA leading global investment firm is seeking a Quantitative Developer to help build and scale the real-time risk, P&L, and market data platforms used directly by Portfolio Managers, Traders, and Quantitative Researchers. This is a front-office engineering role focused on developing the systems that power portfolio analytics, exposure m...
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Quantitative Developer Systematic Investing Platform
A leading quantitative investment firm is seeking an experienced software engineer to build and enhance the technology stack that supports systematic research and trading. The team develops platforms and tools used by quantitative researchers and portfolio managers to generate, test, and deploy investment strategies at scale.This is a highly collab...
Senior Data Engineer
ResponsibilitiesBuild and optimize scalable data pipelines and data products.Develop reliable datasets for analytics, reporting, and AI applications.Establish data engineering standards, frameworks, and best practices.Improve data quality, monitoring, testing, and platform observability.Integrate and reconcile complex datasets from multiple sources...
Senior Data Engineer
ResponsibilitiesBuild and optimize scalable data pipelines and data products.Develop reliable datasets for analytics, reporting, and AI applications.Establish data engineering standards, frameworks, and best practices.Improve data quality, monitoring, testing, and platform observability.Integrate and reconcile complex datasets from multiple sources...