Develop state-of-the art machine learning models to solve real-world problems and apply it 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 promote practical and successful solutions
Required qualifications, capabilities, and skills
BS with 5+ years, or MS with 3+ years of hand-on industry experience in Machine Learning - Deep Learning.
Good understanding of the latest advancement of NLP concepts, such as the 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
Preferred qualifications, capabilities, and skills
2 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-promoten product development