Job Type: Contract
Contract Length: 12 months (potential for full-time)
Pay Range: $120 - $125/hour
Start Date: ASAP
Location: Hybrid (3 days onsite in Boston, MA)
About the Opportunity:
Our client, a prestigious investment firm, is seeking a highly skilled Principal Quant Engineer to join their Quant Solutions team. This project involves driving the design and implementation of advanced applications, proofs of concept, and production-grade tooling to advance portfolio construction, asset allocation analytics, and quantitative research workflows. This is a high-impact role that requires a hands-on software architect and builder who thrives as an individual contributor and is capable of scaling prototypes into production-ready applications.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Technical Leadership: Lead the design and implementation of applications, proofs of concept, and production-grade tooling to support portfolio construction and quantitative research.
- AI & Prototype Conversion: Partner closely with quantitative analysts and portfolio strategists to convert AI-generated prototypes and research artifacts into robust, production-ready applications.
- Data Pipeline Management: Build and maintain data pipelines for portfolio and market data across public and private markets, leveraging existing data ecosystems.
- Quantitative Library Development: Contribute to the team’s shared quantitative library, supporting both existing and new models, analytics, and reusable components.
- Application Support: Support and extend existing applications and dashboards in production while driving the design of new solutions to meet evolving research and decision-support needs.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- 5+ years of full-stack development experience, with deep expertise in Python (including libraries such as pandas and NumPy).
- Strong SQL skills, with experience manipulating large financial datasets and working with financial data platforms.
- A strong quantitative background with hands-on experience applying statistical, time-series, and optimization techniques (e.g., SciPy, Scikit-Learn, cvxpy, statsmodels) to portfolio construction and asset allocation problems.
- Experience in front-end development and UX design, with a preference for Pythonic front-end and visualization libraries (e.g., Plotly, Dash).
- Proficiency with Version Control (Git) and Agentic Programming tools (e.g., GitHub Copilot, Claude).
- Deep understanding of investment management and portfolio composition strategies across asset classes (e.g., fixed income, public/private equity, private credit).
- Demonstrated ability to work autonomously, manage your own time effectively, and partner with business teams to deliver high-quality, scalable code.
- Excellent communication skills to articulate complex technical ideas to both technical and non-technical stakeholders.
- Master’s or Ph.D. in a quantitative or engineering field (Computer Science, Mathematics, Statistics, Financial Engineering, etc.) is highly preferred.
