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I'm a data scientist and risk-modeling professional with a track record of delivering scalable analytics in finance and technology. I thrive at the intersection of quantitative modeling, data engineering, and cross-functional collaboration to turn complex data into actionable business insights. Beyond the numbers, I enjoy teaching and mentoring — from university boot camps to pro-bono data projects — and I stay curious about new techniques in ML/AI, cloud data architectures, and risk management.…I'm a data scientist and risk-modeling professional with a track record of delivering scalable analytics in finance and technology. I thrive at the intersection of quantitative modeling, data engineering, and cross-functional collaboration to turn complex data into actionable business insights. Beyond the numbers, I enjoy teaching and mentoring — from university boot camps to pro-bono data projects — and I stay curious about new techniques in ML/AI, cloud data architectures, and risk management.

Jimmy Q. Tran

Data Scientist, Data Analyst, Web Developer, +2

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I'm a data scientist and risk-modeling professional with a track record of delivering scalable analytics in finance and technology. I thrive at the intersection of quantitative modeling, data engineering, and cross-functional collaboration to turn complex data into actionable business insights. Beyond the numbers, I enjoy teaching and mentoring — from university boot camps to pro-bono data projects — and I stay curious about new techniques in ML/AI, cloud data architectures, and risk management.…I'm a data scientist and risk-modeling professional with a track record of delivering scalable analytics in finance and technology. I thrive at the intersection of quantitative modeling, data engineering, and cross-functional collaboration to turn complex data into actionable business insights. Beyond the numbers, I enjoy teaching and mentoring — from university boot camps to pro-bono data projects — and I stay curious about new techniques in ML/AI, cloud data architectures, and risk management.

Available to hire

I’m a data scientist and risk-modeling professional with a track record of delivering scalable analytics in finance and technology. I thrive at the intersection of quantitative modeling, data engineering, and cross-functional collaboration to turn complex data into actionable business insights.

Beyond the numbers, I enjoy teaching and mentoring — from university boot camps to pro-bono data projects — and I stay curious about new techniques in ML/AI, cloud data architectures, and risk management.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Vietnamese

Advanced

French

Intermediate

Work Experience

Senior Research Associate, Risk Modeling Team at JPMorgan Chase

July 1, 2023 - April 30, 2024

Selected for a critical 9-month technical integration period to migrate credit assets into JPMorgan’s enterprise risk framework after the FDIC-assisted acquisition of First Republic Bank. Managed functional transfer and segment mapping of Commercial & Industrial, Income Property, and Consumer CECL models into CCB and CB divisions. Standardized legacy risk modeling documentation and codebases to comply with Internal Audit and Model Risk Management standards, securing enterprise-level approval for inherited loss-forecasting methodologies. Harmonized legacy R and T-SQL production workflows with JPM’s analytical systems, stabilizing the first consolidated quarterly ACL reporting cycle for the integrated portfolio.

Senior Quantitative Analyst at First Republic Bank

September 1, 2022 - July 31, 2023

Led credit risk enhancements and portfolio analytics during a period of rapid growth and transition. Developed a linear interpolation model linking historical loss rates to unemployment for consumer and business portfolios, replacing a prior architecture with logistic regression and transition matrices. Improved computational efficiency for scenario stress testing by ~7x through optimized R pipelines with multithreading and batch processing. Forecasted lifetime losses on an $8.1B asset base and led a migration of mission-critical databases from on-premises SQL Server to a Snowflake Data Lakehouse, modernizing ingestion pipelines for high-concurrency, cloud-native operation. Identified and excluded non-representative loan data to improve quarterly loss estimates and developed a bilateral CVA/DVA default-probability model for OTC positions. Spearheaded risk estimates for student loan refinance portfolios and onboarded PPP clients during COVID-19.

Quantitative Analyst at First Republic Bank

June 1, 2019 - September 30, 2022

Contributed to the development and maintenance of credit risk models and loss forecasting during a prior tenure. (Details aligned with portfolio risk assessment, model validation, and data preparation supporting risk reporting and regulatory compliance.)

Remote Teaching Assistant, Artificial Intelligence at University of Pennsylvania & edX Boot Camps

July 1, 2024 - January 31, 2025

Guided a 24-week AI cohort, mentoring 17 students on end-to-end machine learning projects (medical image classification, fraud detection) using TensorFlow, scikit-learn, and NumPy. Instructed model optimization, hyperparameter tuning, loss function selection, and evaluation. Taught production ML deployment patterns, containerization with Docker, API integration with Flask, and experimental design for model validation. Managed grading, virtual office hours, and troubleshooting via Slack.

Teaching Assistant, Financial Technology at UC Berkeley Extension & edX Boot Camps

September 1, 2021 - May 31, 2023

Mentored 45+ students across two cohorts, covering Python-based financial modeling and blockchain interaction (Web3.py). Led instruction on cryptographic security, DeFi protocols, Solidity smart contracts, secure wallet architecture, and transaction authorization. Contributed to open-source curriculum on ML-driven fraud and anomaly detection; managed grading and troubleshooting via Slack.

Financial Economics Tutor (ECON 136) at UC Berkeley Student Learning Center

January 1, 2018 - May 31, 2018

Selected as a peer tutor to support undergraduates in Modern Portfolio Theory, CAPM, Black-Scholes, and related fixed income/arbitrage concepts. Conducted weekly tutoring and intensive review sessions for large cohorts, synthesizing complex financial concepts for effective understanding.

Data Fellow at Delta Analytics (CareerVillage.org)

January 1, 2021 - August 31, 2021

Pro-bono term: conducted technical audit of email recommendation engine; proposed NLP matching improvements to bridge engagement gaps. Integrated production-grade unit tests into core repository and developed analytics to identify 'Advice Gaps' for targeted volunteer recruitment.

Data Fellow at Delta Analytics (CareerVillage.org)

January 1, 2020 - July 31, 2020

Second pro-bono term: architected Python/R scraping pipeline ingesting 58,000+ occupation titles, expanding taxonomy and semantic matching by 700%. Built automated ETL dashboard (Metabase) for real-time health metrics; deployed fastText NLP classifier via AWS Lambda to map student questions to career categories at scale.

Senior Research Associate at JPMorgan Chase

July 1, 2023 - April 1, 2024

Selected for a critical 9-month technical integration period to migrate credit assets into JPMorgan's enterprise risk framework following the FDIC-assisted acquisition of First Republic Bank; ensured data integrity and portfolio continuity across integrated systems. Managed the functional transfer and segment mapping of Commercial & Industrial (C&I), Income Property (IP), and Consumer (Secured/Unsecured) CECL models into CCB and CB divisions. Standardized legacy risk modeling documentation and codebases to comply with Internal Audit and Model Risk Management (MRM) standards, securing enterprise-level approval for inherited loss-forecasting methodologies. Harmonized legacy R and T-SQL production workflows with JPM's analytical systems, stabilizing the first consolidated quarterly ACL reporting cycle for the integrated portfolio.

Teaching Assistant, Artificial Intelligence at University of Pennsylvania & edX Boot Camps

July 1, 2024 - January 1, 2025

Guided a 24-week intensive AI cohort, mentoring 17 students on end-to-end machine-learning projects (medical image classification, fraud detection) using TensorFlow, scikit-learn, and NumPy. Instructed on model optimization, hyperparameter tuning with KerasTuner, loss function selection, and evaluation for high-dimensional data. Covered production ML deployment patterns, including containerization with Docker, API integration with Flask, and experimental design for model validation. Managed grading, virtual office hours, and troubleshooting via Slack.