Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in Batch and API technologies: such as batch scheduling (using Autosys and Airflow) and create REST APIs (using FAST API and Flask) leveraging AWS resources including Lambda, S3, EKS and EC2.
Thoughtfully apply advanced analytics and quantitative concepts to support investment needs and develop new solutions.
Domain knowledge in either equities, fixed income or alternative asset classes
Deep understanding of quantitative techniques and methods, statistics and econometrics – including probability, linear regression and time series data analysis
Experience implementing CI/CD and DevOps best practices. Perform Continuous Integration (CI) and Continuous Deployment (CD) pipelines (using Linux and Jenkins), code versioning using GitHub.
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Lead the implementation of a research project through the entire software development lifecycle using a full-stack implementation.
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
Expert in Python with experience across the development stack (full stack)
Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
A creative problem solver and a curiosity fueled by keeping up with advanced methodologies and industry trends, especially in the finance community
Exposure to object-oriented programming (OOP) and design patterns
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python. This includes developing time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms to build investment strategies.
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.