Chris Tran Email & Phone Number

Jersey City, NJ, US

Role: MLOps Engineer at Verisk's Claim Insights & Analytics (CIA)- Developed internal web application for machine learning model deployment and management on AWS ECS using FastAPI, ReactJS and DynamoDB, leveraging CloudFormation for infrastructure as code.- Designed and implemented a robust batch and queue architecture for asynchronous processing.

Jersey City, NJ, US

Role: Machine Learning Engineer (Computer Vision) at Verisk's 3D Visual Intelligence (3DVI)- Developed a comprehensive PyTorch Lightning framework to facilitate efficient training and evaluation of neural networks tailored for computer vision applications.- Built and trained deep learning models, including MobileNet V3, YOLOv5, DeepLab v3, for accurate.

New York, US

• Trained and deployed MobileBERT for document summarization on mobile devices, achiving 5.5x faster speed while attaining 95% of BERT-large’s performance.
• Trained deep learning models (Transformers, CNN, RNN-LSTM) for document classification and named entity recognition tasks to extract information from legal documents, achieving 0.95 F1 score and saving client hundred.
• Pretrained Spanish BERT and ELECTRA models from scratch on 18 GB of Open Super-large Crawled Corpus (OSCAR) using multiple GPUs on AWS EC2 instances, achieving state-of-the-art results on Spanish benchmarks.
• Vectorized documents with pretrained word vectors such as Word2vec, fastText and ELMo to feed classification algorithms
• Researched latest NLP and CV papers on regular basis, reported findings to CTO and wrote codes to reproduce research results.

Brooklyn, NY, US

• Etsy Summer of Vision (ESV) is a 12-week fellowship that pairs students with mentors from Etsy’s Machine Learning teams in order to explore computer vision applications for the future of Etsy’s shopping experience.
• Applied cutting-edge Computer Vision research to improve personalization and image-based recommendations.
• Designed and trained Deep Siamese architecture with PyTorch to extract aesthetic features from listing pictures.
• Performed efficient similarity search with FAISS library to find nearest neighbors for recommendations.
• Trained Faster R-CNN and Mask R-CNN for object detection and instance segmentation for Home & Living pictures.

Ulm, DE

• Developed data preprocessing and regression pipeline to predict yield percentage from production of coils into finished products. The developed LightGBM regressor achieved highly accurate predictions with 4% MAE.
• Performed data labeling, data exploration, data cleaning, feature engineering on coil history, and hyperparameter tuning with cross validation to optimize accuracy of regressor.
• Built web app to deploy developed pipeline that can quickly generate yield predictions for future production.

Long Island City, NY, US

• Provided technical supports to Fortune 500 clients utilizing Tax Series – TTI’s flagship product, an all-inclusive SaaS global data collection, tax compliance and provision software.
• Assisted on implementation engagements for new clients, including performing data collection, integration and setup in Tax Series.
• Conducted essential application diagnostics on client financial data, including periodically generating technical reports, maintaining data integrity and monitoring client databases.
• Conducted in-depth research on tax forms and e-file requirements in 32 states and four foreign countries, helping develop annual enhancement release for Tax Series.
• Performed application testing to determine if software worked as designed, logged technical reports and collaborated with software engineers to build enhancement update for Tax Series.
• Proposed new changes in priority system and data visualization that improved overall efficiency of ticket support reporting.

Niagara University, NY, US

• Tutored nine students in statistics, business analytics and accounting courses.
• Helped students understand class materials, complete homework and build effective study strategies.
• Rated Excellent in all criteria by eight out of nine students.

Niagara University, NY, US

• In three-month research and two-day hackathon, led a team of four students to discover insights from NYC and Boston government data sets and won runner-up prize for best research poster out of 18 participating colleges.
• Cleaned up (missing data, outlier detection, duplications) and integrated (merge, join, subset) large data sets (6 million records) of governmental spending, contracts and KPI metrics.
• Utilized Python and Tableau to perform exploratory data analysis and visualization on payroll distribution and minority-owned businesses’ participation in government contracts.
• Built and ran linear models on SPSS to determine socioeconomic factors affecting government spending.
• Applied statistical techniques to predict government KPI metrics, crime rate and education quality.
• Presented research findings before data scientists and Wall Street veterans.

• Coordinated with marketing teams to develop digital products for tech companies and startups including Uber Vietnam
• Made travel films and wrote travel blogs

Ho Chi Minh City, VN

• Being one of six interns chosen from over 7000 applicants to make a 14-day motorcycle trip from South to North Vietnam fully sponsored by Bitis Hunter, the best sneaker brand in Vietnam.
• Documented the journey via blog posts, photos and films which were featured on Bitis’s social media to tell stories about Vietnamese people, culture and nature, inspiring the youth to travel and explore Vietnam’s beauty.

Master Of Science, Business Analytics (Stem)

Master Of Science, Business Analytics (Stem)

Bachelor Of Business Administration - Bba, Accounting

Economics