Java Developer-Decision Engineering jobs in Chennai at Applied Data Finance

Java Developer-Decision Engineering

Job Title: Java Developer

Number of open positions: 7

Job Number: 1030020

Location: Chennai, India

Department: Technology and Engineering

Job Summary:

We are looking for a strong, well-rounded developer to improve design and upgrade a Decision Engine built using several technologies.
The person will be part of Decision Engineering team that purposefully uses different programming languages for various functions, providing a service layer to communication with a web front-end and various third party data providers
Designs, develops and documents company's proprietary decision engine using Java technologies.
Works with a group of data scientists to build and deploy predictive models in languages like R and Python.
Integrates the business decision logic into the ecosystem of the company's infrastructure to facilitate company operations.
Integrates with Python based web front end and CloudLending (Salesforce.com based) CRM application.
Periodically builds test systems to help validate new models as they emerge from our data science team
Can interact with various other teams, including Marketing, Compliance, Technology, Data Scientists, Customer Service, etc.

Qualification & Experience:

Bachelor of Engineering, preferably in Computer Science/or related fields or Masters, from a premier college
2 to 6 years overall software development experience
Proven hands-on Software Development experience
Proven working experience in Java development
Hands on experience in designing and developing applications using Java EE platforms
Object Oriented analysis and design using common design patterns
Good Understanding of data structures & Algorithms
Hands on multi-threading
Experience in the Relational Databases, SQL and ORM technologies (JPA2, Hibernate)
Experience in the Spring Framework
Experience in developing web applications
Experience with test-driven development

We have a more accurate picture of Alice than other lenders. We use more data, from more sources. We analyze it using the most advanced data science. We can see that she is, in fact, a good risk. So we can lend to her at a risk-appropriate rate.