Develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks such as NLP, speech recognition and analytics, or recommendation systems
Choosing, extending, and innovating ML strategies for various banking problems
Analyzing and evaluating the ongoing performance of developed models
Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
Learning about and understanding our supported businesses in order to drive practical and successful solutions
Requirements & Skills:
MS with 7+ years, or PhD with 4+ years of hands-on industry experience in Machine Learning.
Good understanding of the latest advancement of NLP concepts, such as transformer architecture and knowledge distillation.
Experience in classical ML techniques including classification, clustering, optimization, cross-validation, data wrangling, feature selection, and feature extraction
Ability to design experiments — establish strong baselines, choose meaningful metrics, and evaluate model performance rigorously
Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
Solid written and spoken communication skills
5 years of hands-on experience with virtual assistant model development and optimization
Familiarity with continuous integration models and unit test development
Experience with A/B experimentation and data/metric-driven product development
