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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.
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