Permanent Financial Technology Jobs
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Lead Data Scientist
Company OverviewGlobal insurance and financial services company with over 90 years of history.Provides personal, commercial, specialty insurance, reinsurance, and asset management services.Operates in more than 100 countries and serves a broad range of customers and industries.SummarySeeking an analytics leader to build machine learning and AI solu...
Senior Java Developer
Build the Future of Mortgage InsuranceOur client is reimagining mortgage insurance from the ground up, replacing legacy systems and manual processes with modern software, automation, AI, and cloud-native technology. Our mission is to build the industry's most technology-enabled mortgage insurer through innovative engineering and scalable platforms....
AI Engineer
Applied AI EngineerNYC, hybrid We're partnered with a leading quantitative investment and technology firm that is building out a new generation of AI-powered tooling and looking to hire an AI Engineer to help drive the initiative.This is a highly hands-on role focused on identifying real business problems and building AI-driven solutions that impro...
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Data Analyst
Data Analyst | Quantitative Trading FirmOverviewJoin a leading quantitative trading firm where data, technology, and research drive business performance.Work with large-scale financial, market, vendor, and alternative datasets that support critical business and research functions.Partner with engineers, data professionals, and business stakeholders...
Vice President of Engineering, Investment Data & Analytics
Vice President of Engineering, Investment Data & AnalyticsBoston, MA (Hybrid)Position OverviewLead the strategy, architecture, and delivery of enterprise data and analytics platforms that support investment research, portfolio management, and business intelligence initiatives.Partner closely with investment professionals, quantitative researchers, ...
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...