Overview
At Bucketplace, I delivered measurable OKR impact through production experiments by establishing a reusable experimentation foundation (Query Feature Table, Redis, Server) and shipping end-to-end from PRD/Design Doc through DAG development to production rollout.
Key Achievements
STORE Search Result Page (SRP) – Deals Ranking
- Buyer Conversion: +1.99%
- Click Conversion: +0.83%
- Special-Offer Exposure: +7.35%
Category Product List Page (PLP) – Price 2.0 Ranking
- Buyer Conversion: +11.17%
- Click Conversion: +5.87%
- Exposure: +27.9%
Experimentation Track Record
- 4 total production experiments conducted
- 3 winners shipped to production
- Minimal side effects observed
Technical Approach
Experimentation Infrastructure
The project established a reusable experimentation foundation:
- Query Feature Table: Computed via Airflow DAGs and served through Redis for low-latency access during search request processing.
- Feature Serving Pipeline: Query Feature Table flows through Redis into the ranking server.
End-to-End Delivery Process
Each experiment followed the full delivery lifecycle:
- PRD / Design Doc authorship
- DAG Development via Airflow
- Production Rollout
Hyperparameter Optimization
Developed specialized Grid Search HPO for ranking parameter tuning, with additional tooling from Optuna and Ray Tune. Integrated with the MOHPER framework for multi-objective optimization across CTR, CVR, and exposure metrics.
Tech Stack
- Feature Serving: Redis, Query Feature Table, Feature-Serving-API
- Orchestration: Airflow DAGs
- Search Engine: ElasticSearch
- HPO: Grid Search, Optuna, Ray Tune, MOHPER
- Data Processing: PySpark, Athena
Period
February 2025 - June 2025 | Bucketplace (오늘의집)