Overview
Build and support machine learning models for Wealth Management (WM) use cases within the Analytics & Data organization.
What you'll do
- Develop ML solutions for Wealth Management use cases with guidance from senior team members.
- Experiment with different modeling approaches to improve model performance.
- Collaborate with model risk and validation partners to document and test model behavior and controls.
- Support deployment and ongoing monitoring of models in production with ML Ops and engineering.
- Assist with A/B tests or controlled experiments and summarize results for stakeholders.
- Communicate model outcomes by creating slides or performance readouts for business stakeholders.
What you'll need
- 3+ years of experience in the Machine Learning domain (overall 3–5 years for the associate role).
- Theoretical knowledge and application of ML algorithms (classification, regression, recommender systems, clustering, deep learning).
- Proficiency in at least one programming language (Python, C++, or a related language).
- Experience with code versioning tools such as GitHub or Bitbucket and experiment tracking systems like MLflow.
- Proficiency with computer science fundamentals in OOP design, data structures, and algorithmic design.
- Ability to work independently, solve problems creatively, and debug/maintain complex code.
- Strong oral and written communication skills, including presenting complex information clearly.
Read the full description and apply on the company’s own careers page.
