Quantitative Strategist, Macro Technology at Point72

, , United States -

Full Time

Start Date

Immediate

Expiry Date

15 Jun, 26

Salary

0.0

Posted On

17 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, C++, Quantitative Analytics, Rates, FX, Pricing Tools, Curve Construction, Scenario Analysis, Backtesting, Data Engineering, Cloud Platforms, Data Pipelines, Time-Series Data, Data Modeling, Agile Methodologies, AI

Industry

Financial Services

Description

A CAREER WITH POINT72’S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. 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 backtesting 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. • 12-15+ years of experience in macro quantitative analytics and development at a top-tier bank or 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 backtesting 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, GCP, 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.

Responsibilities

The role involves designing and developing pre-trade pricing and analytics tools for investment professionals supporting Rates and FX products, including implementing real-time pricing engines and historical pricing frameworks. Responsibilities also include building scenario analysis frameworks and integrating analytics into research and trading workflows while contributing to core analytics libraries.