Quant Research Engineer

Job Title: Research Engineer

Location: New York, NY (Remote Option Available)

Position Overview: Our Fintech Client is seeking a skilled Research Engineer with a strong quantitative research background and expertise in financial engineering. This role focuses on developing and maintaining cutting-edge statistical and machine learning models for pricing corporate bonds and enhancing automated trading strategies. Ideal candidates will have experience in building scalable MLOps infrastructure, managing large data sets, and implementing high-impact quantitative models in production environments.

Key Responsibilities:

• Quantitative Model Development: Design, build, and refine statistical models for corporate bond pricing and trading. Apply techniques such as multivariate time series analysis, outlier detection, and machine learning algorithms (e.g., gradient boosting, neural networks).
• Pipeline & Microservices Implementation: Develop and deploy microservices for real-time data processing and pricing, ensuring efficient and reliable performance across diverse trading scenarios.
• MLOps & Model Monitoring: Construct tools and workflows for job scheduling, model versioning, and performance monitoring. Maintain a robust MLOps pipeline for shadow mode deployment, reproducibility, and model integrity (e.g., simulators, feature stores).
• Research & Experimentation: Conduct in-depth research into advanced statistical and machine learning techniques to support ongoing model improvement. Collaborate with other researchers and engineers to integrate innovative solutions.
• Collaboration & Knowledge Sharing: Assist with onboarding new hires, mentor junior team members, and contribute to the recruitment process by reviewing resumes and interviewing candidates.

Qualifications:

• Educational Background: Master’s in Financial Engineering or a related quantitative discipline.
• Programming Languages: Python (NumPy, Pandas, Scikit-Learn, TensorFlow), R, SQL, VBA, Caml
• Technology Stack: Experience with Git, UNIX, AWS, Docker, Kubernetes, Apache Kafka, Airflow
• Mathematical Expertise: Strong foundation in linear algebra, calculus, algorithms, probability theory, optimization, statistics, and stochastic calculus
• Soft Skills: Ability to communicate and work effectively with Traders, Quants, and Business Stakeholders

Preferred Experience:

• Prior experience in financial research, particularly in the Fixed Income Or Corporate Bond space
• Familiarity with MLOps and machine learning model deployment in a production setting

The base range for this role is 150,000 - 225,000. This does not include discretionary bonus or potential equity options.