Quantitative Engineer
Core
Designing, developing, testing, and implementing scalable software components and data pipelines for risk management, surveillance, and testing frameworks.
Role type
Quantitative Engineer (Software Engineering & Big Data)
Builds
Reusable software components, big data pipelines, classification models, and testing frameworks for Global Risk Management.
Domain
Financial Services / Global Risk Management / Big Data
Deliverable
production ML models | product features | infrastructure
Required skills
Python, Software Development Lifecycle, Big Data pipelines, Quantitative methods (regression, classification, clustering), Financial data understanding, Unit/Regression testing
Preferred skills
Machine learning, Statistics, React/Angular/JavaScript, Spark/PySpark/Hadoop/Hive, Process automation, Financial modeling
Technologies
Python, Pandas, Spark, PySpark, Hadoop, Hive, React, Angular, JavaScript, MapReduce, DataFrames
Responsibilities
Apply quantitative methods to meet risk and regulatory requirements; Build performant big data pipelines; Develop high-quality code for model and testing processes; Collaborate with stakeholders to understand modeling business processes; Design and implement models and tests; Source and evaluate data for modeling; Produce technical documentation for internal and regulatory purposes.
Seniority
Mid-level, hands-on IC
