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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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