Data Science Engineer Portfolio Management Vice President

JobID: 210503215

Category: Portfolio Management

JobSchedule: Full time

Posted Date: 2024-05-15T18:23:04+00:00

JobShift:

Base Pay/Salary: New York,NY $161,500.00-$285,000.00

Bring your passion for solving complex AI/ML engineering problems to a high impact role on our investment team. Through a close partnership with a team of portfolio managers and data scientists, your engineering expertise will contribute directly to the future growth and innovation of our products.

As a Data Science Engineer in the Applied Data Science investment team within J.P. Morgan Asset Management, you will collaborate closely with portfolio managers and data scientists on a proprietary data science investment process. You will partner with team members across the full lifecycle of the team's AI/ML projects, helping to solve complex engineering problems from the research stage through to production implementation.

Job Responsibilities:

• Design highly scalable pipelines for data ingestion and data processing

• Deploy efficient inference workflows for large-scale AI models

• Ensure pipeline robustness by constructing effective monitoring workflows

• Integrate datasets across a wide variety of formats

• Remain up to date with the latest developments in AI through research and experimentation

• Partner directly with the team's data scientists to facilitate research projects and production implementation

Required Qualifications, Capabilities, and Skills:

• 3+ years of relevant experience working with large-scale datasets

• Proficiency in programming languages such as Python

• Strong understanding of data science pipelines and relevant technologies

• Hands-on experience with public cloud services

• Intellectual curiosity and passion for problem solving

Preferred Qualifications, Capabilities, and Skills:

• Demonstrated success bringing large-scale pipelines from research to production

• Experience working with AWS services

• Solid understanding of AI/ML models, including previous experience with deep learning frameworks

• Experience working with a variety of data formats, including natural language, image, and time series data