JPMorgan Chase is looking to accelerate its data and analytics journey by ensuring the quality, integrity, and security of the company's data and leveraging this data to generate insights and drive decision-making.
Requirements
- Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods
- Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Experience with big data and scalable model training
- Strong background in Mathematics and Statistics
- Familiarity with the financial services industries and continuous integration models and unit test development
- Knowledge in search/ranking, Reinforcement Learning or Meta Learning
- Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment
Responsibilities
- Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
- Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
- Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
- Design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Develop and debug production-quality code
- Apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems
Other
- PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 3 years of industry or research experience in the field
- Ability to effectively communicate technical concepts and results to both technical and business audiences
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems
- Solid written and spoken communication
- Ability to work both independently and in highly collaborative team environments
