Mengjun Chen

AI Researcher

Vancouver, British Columbia, Canada2 yrs 8 mos experience

AI ML PractitionerHighly Stable

Key Highlights

Enhanced car valuation accuracy by 30% at Autozen.
Developed dashboards for weekly reporting at Meta.
Proficient in Python, SQL, and R for data analysis.

Stackforce AI infers this person is a Data Engineering and Analytics professional in the SaaS industry.

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Skills

Core Skills

Data AnalyticsArtificial Intelligence (ai)Natural Language Processing (nlp)Data EngineeringApi DevelopmentMachine Learning

Other Skills

PythonPython (Programming Language)Deep LearningTableauCommunicationMachine Learning AlgorithmsAmazon Web Services (AWS)Google BigQuerySpreadsheetsText-to-Speech SynthesisMicrosoft AzureMySQLDASHFlaskPlotly

About

As a Data Engineer/Data Analyst at Meta via Teksystem, I work on audio-related projects that test and improve the Text-to-Speech (TTS) and Speech-to-Text (STT) models. I develop instructions and guidelines for audio data acquisition, refinement, and evaluation, and construct dashboards for weekly reporting purposes. I use Python, SQL, and R to perform data wrangling, analysis, and visualization tasks. Before joining Meta, I completed my Master of Data Science degree from the University of British Columbia, where I gained outstanding knowledge of machine learning, deep learning, neural network, and natural language processing (NLP) techniques. I also interned as a Data Scientist at Autozen, a marketplace platform for used cars, where I contributed to and maintained the Autozen Valuation Guru project, which enhanced the car valuation accuracy by 30%. I deployed a range of machine learning algorithms, from linear regression to neural networks, and used Tableau to create clear and easy-to-understand visualizations. I have also obtained the Google Data Analytics Professional Certificate, which demonstrates my proficiency in data analytics tools and methods.

Experience

2 yrs 8 mos

Total Experience

2 yrs 8 mos

Average Tenure

2 yrs 8 mos

Current Experience

Openjobs ai

Data Scientist

Dec 2024 – Aug 2025 · 8 mos · Vancouver, British Columbia, Canada · Remote

 Optimized the algorithm for calculating Company Name Matching with Similarity Scores
using LLM embeddings and statistical methods.
 Designed prompts for title standardization and embeddings to improve data consistency and
search efficiency.
 Designed and set up a database at AWS RDS for scalable data storage solutions.
 Managed AWS EC2 and S3 instances, ensuring seamless infrastructure performance.
 Built ETL pipelines and automated workflows using Airflow, enhancing operational
efficiency.

Data EngineeringPython (Programming Language)

Uyo ai

AI Developer

Jul 2024 – Feb 2025 · 7 mos · Vancouver, British Columbia, Canada · Remote

 Engaged in prompt engineering to fine-tune AI models for enhanced performance.
 Created and maintained APIs for backend integration, streamlining communication between
front-end and back-end systems.
 Collaborated with cross-functional teams to ensure efficient deployment and scaling of AI
models.

Python (Programming Language)API Development

Autozen

Data Scientist Intern(Capstone)

May 2023 – Jul 2023 · 2 mos · Vancouver, British Columbia, Canada · Hybrid

 Worked on the Autozen Valuation Guru project as a contributor and maintainer, with the goal of enhancing used car valuations on Autozen's marketplace platform.
 Applying Data Engineering techniques which include data governance and building data pipelines to
gather, prepare, cleanse, and transform AutoZen data for analysis.
 Applying Data Sciencist techniques to build models for better performance (30% performance).
 Using Tableau for building dashboard to make a clean and easy understand visualization of business solution.
 Deployed a range of machine learning algorithms from linear regression, Decision Trees, and Ensemble
Methods to more advanced techniques like neural networks and deep learning.
 Building a Docker and makefile for further deployment.

Deep LearningMachine Learning

University of washington

Research Assistant

Mar 2021 – Sep 2021 · 6 mos · Hybrid

Analyzing ocean current and Kuroshio trend in Taiwan by Python;
Methodology development for detecting eddies from huge amounts of data from NASA;
Building 3D visualization models to help understand ocean models;
Conducting data processing and analysis of high-resolution ocean model output to understand eddy activity in the Kuroshio;

CommunicationMachine Learning AlgorithmsMachine Learning