Quantitative Engineer
Core
Designing, developing, testing, and implementing scalable software components and data pipelines to enable risk management, capital measurement, and regulatory reporting across financial portfolios.
Role type
Quantitative Engineer (Software Engineering & Big Data)
Builds
Reusable software components, generic data quality tools, classification models, and testing frameworks for Global Risk Management.
Domain
Financial Services / Global Risk Management / Big Data
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Software engineering (SDLC, unit testing), Big data (distributed computing, optimization), Quantitative modeling (regression, classification, clustering), Python (Pandas), SQL/Schema understanding
Preferred skills
Machine learning, Statistics, React/Angular/JavaScript, Spark/PySpark/Hadoop/Hive, Financial modeling
Technologies
Python, Pandas, Spark, PySpark, Hadoop, Hive, React, Angular, JavaScript, MapReduce, DataFrames
Responsibilities
Apply quantitative methods to meet line of business and regulatory requirements; Build performant big data pipelines; Collaborate with stakeholders to design future state of data and analytics; Source and evaluate data for modeling and testing; Design and develop models and tests; Produce technical documentation for internal and regulatory purposes.
Seniority
Mid-level, hands-on IC
