NLU SOFTWARE ENGINEER
We are looking for an NLU Software Engineer with background & experience in natural language processing, quantitative/statistical modeling, data engineering & finance. This positions primary focus will be building quantitative & 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 & statistical modeling with large text & numerical data in finance domains; & developing analytic tools & models to measure the performance of our platforms NLU. The specific project for this role is developing & testing an NLU AI platform for use in Cantonese finance domains. Since the position requires an ability to create, test & troubleshoot natural language for Cantonese-speaking banking customers, fluency in Cantonese is required.
What you will be doing (the job duties):
- Developing quantitative & statistical (machine learning) model libraries to solve challenging problems in natural language understanding, as well as maintaining existing model libraries to ensure expected & correct functionalities;
- Working on large text & numerical datasets in finance domains (e., banking, insurance), & implementing complicated quantitative & statistical models & techniques to learn & uncover new patterns in the datasets;
- Building analytical tools & models to evaluate performance & accuracy of our conversational AI platforms understanding of text & numerical data in banking & insurance domains, as well as quantifying performance, accuracy & attribution;
- Improving our proprietary software platforms speed & accuracy to process large text & numerical data in finance domains, by researching, prototyping, implementing & integrating software components such as statistical model libraries & advanced quantitative techniques;
- Writing code to auto-generate large text & numerical datasets in banking & insurance domains for quantitative & statistical (machine learning) model training/learning; and
- Documenting usage of software libraries related to quantitative & statistical models for both internal uses & external consumption by banking & 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 & statistical models in production to resolve natural language processing problems such as sentiment analysis, text classification, & language identification;
- 1 year or more experience managing & analyzing large amount of text & numerical data in finance domains, & 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 & 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 & Cantonese.