Algorithmic Trading Jobs in New Mexico
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Systematic ETF Trader
Systematic ETF TraderOverviewWe are seeking a talented and driven Systematic ETF Trader to join a high-performing trading team focused on developing and executing quantitative trading strategies across global ETF markets. This role combines systematic trading, quantitative research, and technology to identify market opportunities, build scalable tr...
Fraud Data Scientist
Title: Fraud Data Scientist Compensation: $140k - $165k base + bonus Company Summary: A leading consulting firm is seeking a Fraud Analytics Senior Associate/Data Scientist to help clients across financial services, fintech, and payments strengthen fraud detection capabilities. The role combines fraud strategy, machine learning, and advanced analyt...
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...
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Lead Data Engineer
ResponsibilitiesLead the development of cloud-based data platforms, pipelines, and data products leveraging Python, SQL, Snowflake, and AWS.Build scalable solutions for a variety of data sources, including market, alternative, and enterprise datasets.Enhance the firm's data platform through APIs, automation, metadata management, and emerging AI-dri...
Lead Data Engineer
ResponsibilitiesLead the development of cloud-based data platforms, pipelines, and data products leveraging Python, SQL, Snowflake, and AWS.Build scalable solutions for a variety of data sources, including market, alternative, and enterprise datasets.Enhance the firm's data platform through APIs, automation, metadata management, and emerging AI-dri...
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...