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Data Scientist
| Company | JP Morgan Chase |
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| Location | New York, NY, USA |
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| Salary | $167700 – $210000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Mid Level, Senior |
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Requirements
- Master’s degree in Data Science, Machine Learning, Computer Science, or related field of study plus 3 years of experience in the job offered or as Software Engineer, Machine Learning Engineer, Research Engineer, or related occupation
- Alternatively, a Bachelor’s degree in Data Science, Machine Learning, Computer Science, or related field of study plus 5 years of experience in the job offered or as Software Engineer, Machine Learning Engineer, Research Engineer, or related occupation
- Experience with developing and implementing NLP (Natural Language Processing) algorithms for text processing, sentiment analysis, and named entity recognition using advanced models
- Experience with designing and training language models for text generation and machine translation, using TensorFlow
- Experience with building and optimizing machine learning models for classification, regression, and clustering using libraries, including feature engineering and hyperparameter tuning
- Experience with implementing deep learning models for tasks including NLP by leveraging models including Bert
- Experience with using SpaCy for efficient NLP tasks including tokenization and named entity recognition
- Experience with software development by following best practices such as implementing continuous integration and deployment pipelines using Jenkins or GitHub for automated testing and deployment.
Responsibilities
- Leverage traditional and advanced Machine Learning Methodologies and frameworks to design and develop Machine Learning models based on complex business requirements and translate them into data-driven business solutions
- Design and develop production-quality, highly scalable microservices to incorporate models in business operations, assisting in data-driven decision making
- Participate in design and code reviews with peers and stakeholders to drive the long-term goal for technology platform and tool choices, ensuring security and robustness of solutions
- Collaborate directly with business and technology stakeholders, expanding geographical locations to identify potential data science use cases, ideate solutions, and successfully plan and execute on these solutions, to create business value
- Own and drive initiatives in key application areas of Machine Learning like Natural Language Processing
- Drive the implementation of Machine Learning-based software products and solutions for business applications through all stages of the Data Science lifecycle
- Follow engineering best practices while developing products and solutions to ensure high data quality and reduced redundancy
- Stay current on academic and industry trends to adopt and apply the latest research and state of the art algorithms to existing implementations for solving problems
- Articulate analytical findings in clear and concise deliverables, including presentations, discussions, and visualizations to convey results with business and leadership
- Work independently and collaboratively within the team to achieve the desired outcomes of data science efforts.
Preferred Qualifications
No preferred qualifications provided.
