Data Scientist Lead- Vice President
Join our Corporate Technology Machine Learning team at JPMorgan Chase, where we solve complex business issues like Anti-Money Laundering and Surveillance using data science and machine learning. As a Lead Data Scientist, you`ll shape strategic technology solutions across the firm, working at the intersection of business and technology. You`ll collaborate with colleagues to understand challenges and opportunities, translating these insights into high-quality solutions. Your role will involve enhancing existing technology, identifying new capabilities, and providing clear guidance to your Business Analysis colleagues, all while promoting the values and brand of JPMorgan Chase & Co.
Job Responsibilities
- Lead the build-out of the Country Risk Team’s new data analytics capabilities
- Help to protect the firm by developing new insights that will support senior management in making key country decisions
- Become an expert in the data used by the team, including the ability to efficiently and creatively transform that data into insights
- Develop potential machine learning use cases for the team, to apply to tasks such as data analytics, NLP, 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
Required Qualifications, Capabilities, And Skills
- Master’s degree in a data science-related discipline, plus at least six years of industry experience (or: PhD in a data science-related discipline, plus at least three years of industry experience)
- Extensive experience with data transformation (especially in Python) and analytics
- Experience with continuous integration models and unit test development
- Strong written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems
Preferred Qualifications, Capabilities, And Skills
- Familiarity with the financial services industry and Risk management
- Background in NLP and analytics, personalization/recommendation
- 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 and ability to develop and debug production-quality code
- Some industry experience in implementing machine learning and deep learning toolkits (e.g. TensorFlow, PyTorch, Scikit-Learn)".
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