Our Asset and Wealth Management division is driven by innovators like you who are driven to create technology solutions that make us work more efficiently and help our businesses grow. Its our mission to efficiently take care of our clients wealth, helping them get, and remain properly invested. Across 27 cities, our team of 4,600 agile technologists thrive in a cloud-native environment that values continuous learning using a data-centric approach in developing innovative technology solutions.
We are building the #1 Asset Management Technology platform in the world and we need exceptional, motivated, and world-class talent to join the Portfolio Core Technology team at JP Morgan Asset Management. This role is primarily focused on data science / machine learning. However, you are expected to be versatile and be able to own / implement a use case end-to-end, including compute and data layers; and even lightweight UI prototype to test/validate your model. You must have a passion for writing and testing high quality code.
Job Description:
- You will use analytics and machine learning techniques to improve data quality. The goal is to replace thousands of inference rules that are currently coded and maintained to check for data quality issues.
- You will develop an ML-based framework that helps reconcile data from multiple data providers with their own respective meta-data and mnemonics. The data reconciliation framework needs to understand the semantics of trade and instrument lifecycle and also temporal aspects of the attributes being compared.
- We have hundreds of service providers that provide various services to Asset Management business. You will help develop a scorecard based on the QoS (quality of service) provided by each service provider. You will help develop a framework that captures metrics and then calculates an aggregated score based on various parameters.
- For certain key measures or calculations that we show to our users, we want to assign a confidence measure towards the accuracy of such numbers with associated explanation (through generated text). You will work on an algorithm to not only calculate such confidence measure but you will also work on the data model design for storing and retrieving such data points efficiently.
- You will write test cases using TDD/BDD approach with emphasis on high maintainability.
- You will participate in code review sessions - peer reviews and group reviews. You will provide code review sign-off for your peers code.
- You will demonstrate scalability of your models/algorithms using mock testing frameworks and other tools.
- Technical documentation of your algorithm / models
- Implementing logging, auditability, security, and monitoring features.
- You should be able to build lightweight user interface using Angular or React.
Qualifications:
- MUST: At least a BS degree in Computer Science from a reputed university/college. MS or PhD in Computer Science preferred. Can consider non-CS degrees if there is strong relevant experience.
- MUST: Deep knowledge and expertise in Python programming - you should rate yourself 8 out of 10 or higher and be able to demonstrate during the hiring process.
- Experience programming in Java is a huge plus as we will be writing services in Java but exposed via Rest API. If you have expertise in another language like C# or C++ or Scala and you will be willing to learn Java then that will work too. Exposure to R/Matlab is a plus.
- MUST: Experience working through entire lifecycle of at least one large complex application build-out and delivery for either a large financial organization or a top-class technology product team. Your ML / data science project must be in production for at least 1 year.
- 2-5 years of experience in the role of software engineer. Experience building a truly distributed architecture based system, especially involving large data volumes and real-time distribution will be huge plus.
- Knowledge of CI/CD, DevOps tool chain, and a test-driven approach to agile delivery is expected.
- Experience with implementing middle-tier data caching solutions (e.g. Gemfire or Apache Ignite) and/or designing/delivering messaging-based solutions (e.g. Kafka) is a plus.
- Knowledge of modern architectures based on microservices, REST APIs, NoSQL stores (e.g. Cassandra), and event-based architecture will be key.
by via developer jobs - Stack Overflow
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