AI Quantitative Developer
- Source: LinkedIn
- Selby Jennings
- $200,000 to $250,000 /yr
- On-site
- New York City
- Full-Time
- Mid level
Job Description
Summary:
A longstanding, well-established PM pod within a leading multi-strategy hedge fund is seeking a AI Quantitative Developer to work directly with the PM and broader investments team. Following strong performance and increased capital allocation, the team is expanding its research capabilities across thematic equities and macro investing, creating an opportunity for someone who can combine AI expertise, quantitative rigor, and commercial investment thinking.
Responsibilities:
- Build front-office research tools, dashboards, screeners, and workflows that enhance the investment process.
- Leverage AI, machine learning, and statistical techniques to identify actionable market insights.
- Analyze high-volume alternative and fundamental datasets to uncover thematic trends.
- Support investment research across AI-related industries, technology, macro themes, and public equities.
- Automate research processes and improve workflow efficiency for portfolio managers and analysts.
- Translate complex technical findings into commercial investment insights.
Ideal Candidate:
Candidates will typically demonstrate strengths across at least two of the following three areas:
- Native AI Expertise: Deep understanding of AI technologies, infrastructure, hardware, and industry developments.
- Front-Office Development: Experience building practical tools and workflows that directly enhance investment research and decision-making.
- Statistics & Quantitative Analysis: Strong analytical capabilities with experience extracting signals and insights from large datasets.
Requirements:
- Approximately 5+ years of relevant experience within a front-office environment.
- Proven experience working directly with Portfolio Managers, Quantitative Researchers, Traders, and Investment Analysts to develop tools, research workflows, and analytical capabilities that support investment decisions.
- Native AI background with hands-on experience in AI/ML, LLMs, AI infrastructure, semiconductors, data centers, or related technologies.
- Strong programming skills in Python and modern data analytics tooling.
Skills
- Python
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