JPMorgan Treasury/Chief Investment Office – Data & 

United States, New York 

943547402

As a Data & Analytics Solutions Engineer – Associate, you will support the creation of state-of-art solutions for the Investment Portfolio and Asset Liability Management group.

Job responsibilities:

• Design and develop end to end analytical solutions and subcomponents such as data engineering pipelines, python libraries, rest api's, and dashboards
• Participate in the application of modern software engineering practices to architect and build a public cloud native analytics platform
• Assist in the collection of user requirements from Portfolio Managers and Strategists
• Facilitate the use of resulting models and systems across multiple lines of business, including training inexperienced users and hosting informational teaching sessions on the use of analytical tool kits and internal quantitative models
• Consult on the application of modern data science and machine learning to business initiatives.

Required qualifications, capabilities, and skills:

• 3+ years of industry experience and proven track record of leading a team in designing, building, and deploying production grade software in the finance domain
• Prior exposure to accounting standards and fixed income products
• Education/Experience in Computer Science, Engineering, and/or Data Science related discipline
• Strong problem-solving skills and ability to transforming practices into more efficient solutions/system/processes
• Familiarity with building and hosting images and using container orchestration frameworks
• A strong interest in the finance/banking industry

Preferred qualifications, capabilities, and skills:

• Proficiency in at least one high level programming language like Python (preferred).Additional experience in front end development using JavaScript / TypeScript is preferred
• Knowledge and experience in cloud architecture and solutions deployment - preferably using tools like Jenkins, Terraform, Kaniko, and Spinnaker
• Experience with full stack development is preferred
• Experience with data science practices is preferred: regression, classification, clustering simulation, scenario analysis, optimization, etc.