COMPANY DESCRIPTION:
We are part of a new startup within the organization that leverages financial expertise, cutting-edge technologies, and innovation to solve critical problems for the world's leading financial institutions and corporations. Our engineers focus on helping clients address regulatory and operational challenges arising from KYC (know your customer) and AML (Anti money laundering).
We have built a product designed to facilitate the communication and document exchange between parties to fulfill Know Your Customer (KYC) regulatory laws. The platform enables the secure transfer of documents and data while making the process more efficient so entities can start trading sooner, gaining a competitive edge in the industry.
JOB DESCRIPTION:
You will play a critical role in the development of a portfolio of rapidly increasing web-based products and APIs that facilitate secure document exchange and permissioning (Entity Exchange), data cleansing and verification (Entity Verification), and screening peps, sanctions and adverse media (Entity Screening). You will also focus on building models that extract entities, relationships among them, and pertinent intelligence from a diverse array of data-sets in the financial and regulatory ecosystems.
- Identify and formulate various challenges in AML and KYC domains as Machine Learning (ML) problems.
- Design, develop, and validated proposed ML solutions.
- Deploy these solutions on a large scale where performance and maintainability are critical.
Our customers use this information in making crucial decisions; it is paramount that our systems have high precision, accuracy, and low latency. As a member of this team, you will tackle a very interesting set of computational problems such as search and retrieval, document classification, named entity recognition (NER) and disambiguation (NED)
CANDIDATE REQUIREMENTS:
- 2+ years of industry experience in IR (Information Retrieval) / ML / NLP (Natural Language Processing) domain (required)
- Good knowledge of latest advances and best practices in academia and industry (preferred)
- Experience with Big data technologies such as Spark and Hadoop (preferred)
- Experience with Deep learning (preferred)
- Understanding of AML or KYC (preferred)
- Publications in top-tier conferences or journals (desired).