Dan Chen
Summary
Experienced data scientist skilled in analyzing large datasets and providing actionable insights for complex business challenges. Proficient in distribution, predictive and hypothetical modeling. Collaborative and adept at statistical consultation with diverse stakeholders. Proven track record of enhancing company operations.
Overview
9
9
years of professional experience
Work History
Data Scientist
Intel
Hillsboro, Oregon
05.2021 - Current
- Provided statistical consultation to engineers from various backgrounds on topics including experiment design, process change data analysis, process control systems, JMP JSL coding, machine learning modeling for factor screening, output optimization, and path finding.
- Researched, developed, and implemented cutting-edge machine learning methods in process control, including multivariate control charts to detect OOCs in marginal parameters and parameter correlations. Also, researched, developed, and piloted both offline and online data anomaly detecting algorithms to detect changes/excursions in data in a fast and timely manner with customizable capability of adjusting alarm rate based on customers' needs.
- provided training to engineers of various backgrounds on classes including Stat Basics (baseline comparison, multi-group comparison, etc.), Design of Experiments ((full/fractional) factorial design, custom design, response surface methodology, etc.), Process Control Systems, Intro to Modeling, Clustering Analysis, Variation Calculations, JMP, etc..
- Reviewed whitepapers on a daily basis to check qualification plans of tools/process changes, experiments, and data summaries.
Sr Credit Risk Modeling Analyst
BECU
Tukwila, WA
03.2021 - 05.2021
- Model validation on various vendor models regarding various types of model risks.
Model Risk Analyst
Umpqua Bank
Portland, Oregon
02.2020 - 02.2021
- Validated models from various sources including vendor and in-house, across all tiers. A typical validation process includes reviewing input data quality (sampling process, missing data imputation, population stability, manipulation of outliers, etc.), reviewing conceptual soundness and design of model (modeling technique, model development, variable selection , model selection, model estimation, assumptions, and limitations), reviewing the accuracy and stability of model (outcome analysis, backtesting, benchmarking, sensitivity analysis, stability/uncertainty analysis, data quality monitoring, etc.), verifying the implementation and process of model (management challenge, performance testing, ongoing model monitoring, system and change controls, archiving and backup, etc.)
Risk Modeling Intern
Genworth Financial Mortgage Insurance
Raleigh, NC
05.2015 - 03.2018
- Built and maintained credit risk models. Developed probability of default (PD) model and loss given default (LGD) model for both long term market monitoring and product pricing.
- Documented various types of in-house models.
- Conducted ongoing monitoring of model performance and improved model performance with relatively recent data.
Education
Ph.D. - Statistics
North Carolina State University
Raleigh, NC08-2019
Skills
- Research and tool development
- Coding (R, Python, SQL, JSL)
- Experiment Design
- Statistical Analysis
- Statistical Consultation
- Data Mining
- Machine Learning
- Modeling
Timeline
Data Scientist
Intel
05.2021 - Current
Sr Credit Risk Modeling Analyst
BECU
03.2021 - 05.2021
Model Risk Analyst
Umpqua Bank
02.2020 - 02.2021
Risk Modeling Intern
Genworth Financial Mortgage Insurance
05.2015 - 03.2018
Ph.D. - Statistics
North Carolina State University