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AI System Builder & Strategist

Flora
Gong.

Shanghai → New York
Also known as: 💃 Ballroom Dancer 🏃 Marathon Runner 🥊 Boxer 🚴 Biker 🎭 Cosplayer · Model 🐱 Cat Mom
New York · AI SaaS · FinTech
CRM Architecture · Tiered Pricing · LLM Orchestration
Python SQL LangChain A/B Testing
At a Glance
40%
Platform capacity scaled by architecting CRM ecosystem & matter lifecycle for 10k+ assets
15%
Revenue lift driven by AI scoring signals & high-probability recovery prioritization
70%
Reduction in manual data entry via LangChain + Claude automated classification engine
Monetaria LLC
Project Manager, Data Product & Analytics — Private Credit Solutions Portal
May 2025 – Present  ·  New York
Platform Scale
+40%
Revenue Lift
+15%
Manual Work ↓
−70%
Conversion
+10%
Research & Analytics
Masterworks
Data Scientist — Research & Analytics
May 2022 – Dec 2023  ·  New York
  • ML Fine-tuned Transformer models and engineered a hybrid CNN + OLS pipeline for art market time-series forecasting; built a hedonic pricing index for investment valuation under volatile conditions.
  • Multimodal Trained large-scale models on image + text description datasets for automated artwork classification and valuation; owned the full ML lifecycle from data labeling to model evaluation.
  • MLOps Dockerized and deployed ML microservices; architected AWS Redshift pipelines and Apache Airflow DAGs to automate ETL from S3 for marketing attribution and financial reporting.

As a Data Scientist on Masterworks' Research team, I developed the proprietary ML valuation models and ETL pipelines that powered the platform's art market analysis — the core technology behind the company's growth to $882M AUM and 800,000+ members, as covered by ARTnews, CNBC Select, and Morning Brew.

$882M
AUM at Peak
800K+
Members
92%
ML Model Accuracy
250+
Artworks Acquired
Core Capabilities

What I Do.

Machine Learning
Predictive modeling, NLP, computer vision, HITL systems, and production-grade valuation models.
Experimentation
End-to-end A/B and multivariate testing — metric definition, power analysis, significance, and impact readout.
Product Analytics
Metric frameworks, funnel optimization, retention modeling, KPI design, and cross-functional decision intelligence.
Data Engineering
ETL pipeline architecture with SQL and Airflow, OCR data pipelines, automated scoring systems built 0→1.

Tech
Stack.

Core Skills
Python pandas · PyTorch · sklearn · OCR
LangChain / LLMs LLM orchestration · Claude · prompt engineering
SQL complex queries · ETL · AWS Redshift
ML / Modeling Transformers · CNN · OLS · Time-Series
Tableau dashboards · forensic flows · KPI reporting
Tools & Platforms
Docker Kubernetes Airflow AWS Redshift Git / GitHub n8n Jira Salesforce REST APIs
Domains
AI SaaS FinTech Private Credit Alt Assets Product Analytics
Education
MBA
Trine University
M.B.A. (In Progress)
New York
2025 – Present
3.91
New York University
Tandon School of Engineering
M.S. Data Science & Urban Informatics
New York
Sep 2021 – Sep 2022
3.75
Fudan University
B.S. Data Science
Shanghai · Top 3 in China
Sep 2017 – Sep 2021
Research & Publications

Published
Work.

ICAHN 2025 IEEE Computer Society pp. 43–46
Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs
Large language models (LLMs) have shown great potential in medical question answering (MedQA), yet adapting them to biomedical reasoning remains challenging due to domain-specific complexity and limited supervision. We study how prompt design and lightweight fine-tuning affect the performance of open-source LLMs on PubMedQA, a benchmark for multiple-choice biomedical questions. Focusing on instruction prompts and Chain-of-Thought (CoT) prompts with QLoRA, our experiments show CoT prompting can improve zero-shot reasoning while instruction tuning significantly boosts accuracy — with benefits that are model- and scale-dependent. Our study offers practical insights into combining prompt engineering with efficient fine-tuning for medical QA applications.
Chenqian Le  ·  Ziheng Gong  ·  Chihang Wang  ·  Haowei Ni  ·  Panfeng Li  ·  Xupeng Chen
New York University  ·  Columbia University  ·  University of Michigan
DOI: 10.1109/ICAHN67688.2025.00016
Read Paper
Beyond the Code

Creative
Works.

Available for Opportunities

Let's Build
Something.

Open to Product Data Scientist, Data Scientist, and Analytics Engineering roles in New York.

New York City  ·  LinkedIn