NLU SOFTWARE ENGINEER
We are looking for an NLU Software Engineer with background and experience in natural language processing, quantitative/statistical modeling, data engineering and finance. This positions primary focus will be building quantitative and statistical model libraries to solve complex challenges of natural language understanding (NLU) in our conversational artificial intelligence (AI) software platform; tackling challenging problems in quantitative and statistical modeling with large text and numerical data in finance domains; and developing analytic tools and models to measure the performance of our platforms NLU. The specific project for this role is developing and testing an NLU AI platform for use in Cantonese finance domains. Since the position requires an ability to create, test and troubleshoot natural language for Cantonese-speaking banking customers, fluency in Cantonese is required.
What you will be doing (the job duties):
- Developing quantitative and statistical (machine learning) model libraries to solve challenging problems in natural language understanding, as well as maintaining existing model libraries to ensure expected and correct functionalities;
- Working on large text and numerical datasets in finance domains (e., banking, insurance), and implementing complicated quantitative and statistical models and techniques to learn and uncover new patterns in the datasets;
- Building analytical tools and models to evaluate performance and accuracy of our conversational AI platforms understanding of text and numerical data in banking and insurance domains, as well as quantifying performance, accuracy and attribution;
- Improving our proprietary software platforms speed and accuracy to process large text and numerical data in finance domains, by researching, prototyping, implementing and integrating software components such as statistical model libraries and advanced quantitative techniques;
- Writing code to auto-generate large text and numerical datasets in banking and insurance domains for quantitative and statistical (machine learning) model training/learning; and
- Documenting usage of software libraries related to quantitative and statistical models for both internal uses and external consumption by banking and insurance clients.
What you will need (our minimum requirements):
- Masters degree or higher in finance, economics, financial engineering, financial mathematics, computational linguistics, or other related fields;
- 1 year or more of experience deploying quantitative and statistical models in production to resolve natural language processing problems such as sentiment analysis, text classification, and language identification;
- 1 year or more experience managing and analyzing large amount of text and numerical data in finance domains, and applying statistical model libraries to the datasets;
- 1 year or more experience in a natural language processing setting (g., sentiment analysis, text classification, etc.);
- Demonstrated proficiency using Java and Python object-oriented programming languages;
- Demonstrated proficiency with one or more of the following database software languages: MySQL, PostgresSQL, MS SQL, or MongoDB;
- Demonstrated proficiency with one or more of the following statistical software programs: MATLAB, SAS or Python; and
- Fluency in both English and Cantonese.
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