# Placeholder Name - Recommender System Algorithm Engineer
Source: https://hello.cv/qiangwang
Beverly Hills

## About
Highly analytical Recommender System Algorithm Engineer with expertise in designing, developing, and deploying advanced machine learning models to enhance user engagement and drive business growth. Proven ability to optimize large-scale recommendation systems, leveraging deep learning and collaborative filtering techniques to deliver personalized experiences and measurable improvements in key performance indicators.

## Work
### Recommender System Algorithm Engineer | Leading Tech Company
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Designed and implemented cutting-edge recommender system algorithms to enhance user experience and drive key business metrics for a high-traffic digital platform.
- Developed and deployed a novel deep learning-based recommendation model, increasing user engagement by 18% and content consumption by 12% across core product lines.
- Optimized real-time inference pipelines for scalable recommender systems, reducing latency by 25% and improving throughput to serve over 50 million daily recommendations.
- Conducted rigorous A/B testing and statistical analysis on new algorithm iterations, leading to the adoption of features that boosted conversion rates by 7% and revenue by 5%.
- Engineered impactful features from large-scale user behavior and item metadata, improving model accuracy (e.g., 15% reduction in RMSE) and personalization effectiveness.

## Languages
- English

## Skills
### Machine Learning & AI
- Recommender Systems
- Collaborative Filtering
- Content-Based Filtering
- Deep Learning
- Matrix Factorization
- Natural Language Processing (NLP)
- Computer Vision
- Reinforcement Learning
- A/B Testing
- Experimentation Design
### Programming & Tools
- Python
- TensorFlow
- PyTorch
- Scikit-learn
- Spark
- Hadoop
- SQL
- NoSQL
- Git
- Docker
- Kubernetes
- Jira
### Data & Cloud Platforms
- Big Data
- Data Science
- Data Modeling
- Feature Engineering
- MLOps
- AWS
- Google Cloud Platform (GCP)
- Azure
- Distributed Systems

## Source
Read this profile on Hello.cv: https://hello.cv/qiangwang
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