Key responsibilities include:
- Understanding financial data: schemas, flow, size, data issues, data controls, etc.
- Building performant big data pipelines that are the backbone of building large scale surveillance systems.
- Building surveillance models using sophisticated modeling techniques including machine learning and AI.
- Testing the efficacy of surveillances using advanced modeling techniques.
Required Skills:
- Successful candidates will have a Bachelor’s or Master’s degree in computer science or related disciplines.
- At least 2 years of relevant experience in software engineering in Quantitative Finance or other industries.
- Ability to analyze and find interesting patterns in data with at least one of the following:
- Experience in implementing distributed algorithms on large amounts of data using Big Data, batch and streaming technologies like Hadoop, Spark, Flink, Kafka etc.
- Experience in building user facing applications over large amounts of data using technologies like React, Angular, JavaScript etc.
- Experience with SQL and NoSQL databases such as MongoDB, HBase, Cassandra, Oracle etc. to process large scale data.
- Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences.
- Ability to effectively present findings, data, and conclusions to senior leaders.
- Ability to operate independently with minimal supervision to deliver sub tasks as well as ability to participate in group settings.
Preferred skills:
- Experience in machine learning / AI models
- Experience with large scale financial data sets
- Experience to code independently with minimal oversight in at least one programming language like Python or Java.
Minimum Education Requirement:Successful candidates will have a Bachelor’s or Master’s degree in computer science or related disciplines.
1st shift (United States of America)