Client REQUIRES 1-2 days a week in their Boston office
My client is seeking a highly skilled Python/Quant Engineer to spearhead a comprehensive, multi-year initiative focused on the redesign, reverse engineering, and modernization of their investment and research platform. This platform is essential for researchers, providing the infrastructure for data processing, model development, and seamless integration with systems like Aladdin. The project will involve a significant re-write from MATLAB to a cutting-edge Python environment.
Ideal Candidate Profile:
The successful candidate will possess a robust background in advanced mathematics, statistical modeling, and time series analysis, enabling them to design and architect core libraries and foundational components of the platform. This role requires an experienced problem solver, capable of building solutions from the ground up rather than merely implementing existing Python frameworks. Advanced expertise in differential equations, statistical analysis, and optimization is essential, as well as a demonstrated ability to craft optimized and efficient code architecture.
This is not a Python practitioner role; rather, it calls for a "Python Rockstar"-someone capable of bridging the gap between business objectives and technical implementation, designing a forward-looking platform that meets complex research needs in equities and fixed income. Your focus will be on writing and architecting new code, with operational considerations playing a secondary role.
Position Overview
We are looking for a skilled Quantitative Developer to collaborate with systematic investing teams on enhancing various stages of the investment process, including data ingestion, research tools, and model analytics. You will develop and implement data processing and quantitative tools in Python, leveraging a cloud-native, scalable computing platform. Working closely with Researchers and Portfolio Managers, you'll support the team's investment processes, from model development to portfolio construction, gaining a deep understanding of quantitative models and the key drivers of investment decisions.
Key Responsibilities
Quantitative Development: Develop, enhance, test, and deploy production model code to support our research platform and strategy applications.
Quant Operations: Collaborate with researchers and investment professionals to provide operational support for running quantitative models.
Platform Migration: Contribute to migrating code to a new Python-based research platform, proposing modern architectures in partnership with the Technology team.
Software Engineering: Apply best practices in software design and implementation, lead code reviews, perform code analysis, and identify potential software risks proactively.
Data Pipeline Management: Design and build efficient data and analytics solutions using a Python stack to meet internal business needs.
Team Collaboration: Actively engage in Python platform working groups and agile/scrum activities to support team goals.
Application Development: Design and develop complex software applications using MATLAB and Python to support internal business requirements.
Qualifications
Bachelor's degree required; advanced degree in computer science, data science, engineering, math, or a related field preferred.
Familiarity with statistics and optimization libraries (e.g., cvxpy, Gurobi) is helpful.
Proficiency in Python, including package development, with 3-5 years in Python and 7+ years of full-stack development experience.
Strong understanding of software design principles.
Experience with SQL and relational database development preferred.
Proficiency with version control tools, especially Git.
Experience with CI/CD, DevOps, and orchestration tools like Azure DevOps, Airflow, Kubernetes, and Docker is a plus.
Familiarity with cloud-based data platforms such as Databricks, Synapse, or Data Lakehouse is beneficial.
Solid knowledge of multi-asset classes, with a focus on equities, is required.
Client WILL PAY for relocation from out of state candidates