What are the responsibilities and job description for the Data Scientist, Sr Associate position at JPMorgan Chase?
The Corporate Data and Analytics Services (CDAS) Elite AIML organization, solves challenging business problems using data science and machine learning techniques across Corporate technology and the supported Corporate Functions.
As a Data Scientist in this team, you will build effective, scalable, and modern analytical solutions for various banking domain problems and deploy them into production business workflows. This is an exciting opportunity to work alongside a world-class group of Data Scientists and Machine Learning Engineers and have profound influence on the business and technology processes of the firm. You will have broad areas of ownership including but not limited to stakeholder engagement, data mining, insights delivery, training and deployment of machine learning/LLM solutions as well as the ability to influence entire organizations. All in a modern data and development environment.
Job Responsibilities
- Developing new insights by understanding the business and data to support senior management in making key decisions
- Become an expert in the data used by the team, including the ability to efficiently and creatively transform that data into insights
- Identify strategic machine learning use cases for the team, and apply to tasks such as data analytics, summarization and question answering, time-series prediction, fraud detection, customer life cycle management, 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 four years of industry experience (or: PhD in a data science-related discipline, plus at least two years of industry experience)
- Extensive experience with data analysis and 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
- Experience with A/B testing 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 as well as deep learning toolkits (e.g. TensorFlow, PyTorch, Scikit-Learn)
