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# Quantitative Developer, Quantitative Strategies

- **Company:** MILLENNIUM
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Data Architecture, Data Infrastructure, Data Systems, Data Warehousing, Software Design Patterns, Linux, Python (Programming Language), Performance Tuning, SQL Databases, Snowflake, Kubernetes, Production Code, Dask, Slurm, Virtual Agents, Data Pipelines
- **Published:** May 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c33bf79ca174920d

## About the Role

Do you have experience in Tooling?, * Strong Python engineering skills, with the ability to write clean, scalable, production-quality code

 * Experience with performance optimization in Python and with parallel / distributed workloads
 * Familiarity with tools such as Kubernetes, Ray, Dask, Polars, Slurm, or similar distributed compute / orchestration frameworks
 * Experience with SQL; familiarity with modern data warehouses such as Snowflake is a plus
 * Strong Linux experience
 * Solid understanding of system design, design patterns, and data architecture
 * Excellent communication, analytical, and problem-solving skills, with the ability to quickly understand and implement complex quantitative workflows

Preferred Experience

 * 3+ years of experience as a quantitative developer, research engineer, or software / data engineer, ideally in a systematic trading or financial context
 * Experience building or supporting research platforms, simulation frameworks, or quantitative data infrastructure
 * Experience creating, organizing, and maintaining custom datasets and production-grade data pipelines
 * Experience supporting the deployment, monitoring, and maintenance of live research outputs or trading models
 * Experience working closely with researchers in a fast-paced, iterative environment

## Description

We are seeking a highly skilled, entrepreneurial Quantitative Developer to join an existing collaborative quantitative trading pod. This is a hands-on role at the intersection of technology, data, research, and trading, with direct exposure to the Senior Portfolio Manager and quantitative researchers. The role spans the full systematic trading stack, with a particular focus on research infrastructure, data systems, signal deployment, and production monitoring., * Own and continuously improve the team's research platform, including the backtesting framework, simulation environments, and caching / compute layers

 * Build and maintain tooling that enables researchers to develop, test, and deploy signals efficiently
 * Integrate Agentic AI workflows where they can improve productivity, model development, or operational robustness
 * Design, organize, and maintain large-scale datasets and data pipelines used across research and production
 * Optimize and support the team's interfaces with central and external systems, including execution, risk monitoring, and compute / resource management
 * Help productionize and monitor trading signals, ensuring robustness, observability, and operational reliability
 * Partner closely with researchers and the SPM to translate research needs into scalable engineering solutions


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