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Quantitative Strategist (Macro Data Analytics)
StrivectorNew York, NY🇺🇸United StatesPosted 13 Jul 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
Title: Quantitative Strategist (Macro Data Analytics)
Location: New York, NY
Position Type: Fulltime/Permanent
Job Description:
What you’ll do
- Design and develop pre-trade pricing and analytics tools for investment professionals, supporting Rates and FX products.
- Implement real-time pricing engines and historical pricing frameworks using market and trading data.
- Develop analytics for historical curve construction, curve evolution, and relative value analysis.
- Design, generate, and maintain large-scale derived macro datasets for trading analytics, ensuring consistency, performance, and reusability across workflows.
- Build scenario analysis frameworks allowing investment professionals to define shocks and assess pricing and PnL impacts.
- Integrate pricing, scenario, and back testing analytics into research and trading workflows.
- Develop scalable data pipelines for historical market data ingestion, normalization, storage, and retrieval.
- Collaborate with investment professionals to translate trading ideas into quantitative analytics and tooling.
- Contribute to the firm’s core analytics libraries and data architecture, with a focus on robustness, performance, and extensibility across asset classes.
What’s required
- Post-graduate degree in a quantitative discipline from a top-tier university.
- 8-15+ years of experience in macro quantitative analytics and development at a top-tier fund.
- Strong expertise in linear Rates and FX products, including curve construction, pricing, and relative value.
- Proven experience building pre-trade analytics, trading pricing tools and research platforms.
- Strong understanding of back testing frameworks, historical analysis, and scenario-based research.
- Advanced programming skills in Python and C++.
- Solid data engineering and analytics proficiency, including experience with large financial datasets and time-series data.
- Proven experience building and persisting derived data at scale, including data modeling, storage, and access patterns for quantitative research and production analytics.
- Hands-on experience with cloud-based data and analytics platforms such as AWS, Google Cloud Platform, and/or Azure.
- Experience designing and maintaining production-quality data pipelines and analytics services.
- Strong communication skills and a demonstrated ability to work closely with investment professionals.
- Commitment to the highest ethical standards.
Skills
AWS
Linear
Azure
C++
Google Cloud
Python
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