Create, research, implement, and maintain state of the art machine learning models, data pipelines, and analytical systems to significantly enhance our investment processes and outcomes
Conduct applied research into financial modeling to help our investment professionals make better decisions
Collaborate directly with senior investment professionals and fellow technology associates to enhance our investment process through the use of state-of-the art ML techniques
Design, research, build, deliver and operate machine learning systems, data pipelines, and financial models which demonstrably improve the efficiency and effectiveness of CG’s investment process by making investment decisions
Research, train, evaluate and deploy models for financial modeling and data analysis from inception to deployment and operation
Uphold a high standard of quality in your work, ensuring integrity in both form and function
Write clear, efficient, and performant code
Collaborate effectively to support team strategy, contributing to decisions regarding modeling and technology
Proactively identify and tackle the root causes of endemic modeling problems, collaborating with cross-functional teams to implement sustainable solutions
Work with a sense of urgency, and design and build simple and pragmatic solutions which solve complex problems

3+ years of experience with Python and SQL
Strong object-oriented or functional design skills with understanding of common design patterns
Demonstrated track record in one or more machine learning subfield relevant to financial modeling, such as time series analysis, quantitative modeling, optimization, anomaly detection, or predictive analytics
Experience solving "full stack" machine learning problems, from data collection and ETL development to model training and deployment
Strong communicator with the ability to establish and maintain a close working relationship with distributed team members and business partners
Strong computer science fundamentals including data structures, algorithms, and complexity analysis
Knowledge of software engineering best practices (e.g. Agile software development, test-driven development, unit testing, code reviews, design documentation)
Track record of successfully delivering enterprise-grade models into production
Experience with AWS services (S3, containers – ECS & EKS, Lambda) preferred

Machine Learning Engineer II

Key skills