Summary

Quantitative and business-focused Senior Data Scientist with 6+ years of experience developing production machine learning models, statistical inference frameworks, and deep learning algorithms. Specialized in end-to-end ML lifecycles—from exploratory data analysis and feature engineering to model deployment (MLOps) and continuous monitoring. Proven history of generating $14M in incremental revenue, cutting customer churn by 22%, and improving classification inference accuracy by 34% across high-scale SaaS and FinTech environments.

Work experience

Senior Data Scientist

Aug 2022 - Present

QuantumEdge Analytics

• Boston, MA

Led the algorithmic development of a real-time recommendation engine using PyTorch and XGBoost, increasing click-through rates (CTR) by 26% and driving $8.5M in annual ARR. Designed and launched a causal inference and A/B testing framework evaluating over 40 concurrent product experiments across 4M+ monthly active users. Built an enterprise customer churn prediction pipeline with LightGBM and FastAPI; integrated predictions into CRM workflows, reducing churn by 22%. Established automated MLOps pipelines using MLflow and AWS SageMaker to track experiments, manage model registries, and automate retraining upon data drift detection. Mentored a team of 4 data scientists, overseeing code reviews, model validation standards, and research-to-production transitions.

Junior Data Scientist

Jun 2018 - Jun 2019

Horizon Analytics Group

• New York, NY

Built multivariate time-series forecasting models using Prophet and ARIMA to project seasonal inventory demand, reducing stockout events by 14%. Wrote high-efficiency SQL queries and Python scripts to extract, clean, and normalize structured data from PostgreSQL databases. Partnered with product managers to deliver weekly statistical scorecards and cohort retention summaries.

Projects

Domain-Adapted RAG Knowledge Assistant

Jan 2024

Designed and deployed a Retrieval-Augmented Generation (RAG) system grounded on 100K+ proprietary technical documents, reducing hallucination rates to below 2% and serving sub-second inference via FastAPI.

End-to-End Dynamic Pricing Engine

Jan 2024

Built a simulation platform modeling price elasticity of demand across multi-tier SaaS offerings, identifying optimal pricing tiers that increased simulated margins by 11%.

Skills

PythonMachine LearningDeep Learning & NLPPyTorchTensorFlowSQLStatistical Modeling & ExperimentationApache Spark (PySpark)MLOps & Deployment

Certifications

AWS Certified Machine Learning – Specialty

Jan, 2024

Amazon Web Services

TensorFlow Developer Certificate

Jan, 2022

Google

Education

Master of Science in Data Science / Machine Learning

Jan 2016 - Dec 2018

Columbia University

Bachelor of Science in Applied Mathematics & Statistics

Jan 2012 - Dec 2016

Boston University