Citlalli Blanchet

About Citlalli Blanchet

I am a Data Scientist with an actuarial foundation, working at the intersection of insurance risk analytics, machine learning, and applied statistical modeling. I combine the quantitative rigor of actuarial science with the practical, hands-on modeling and pipeline development skills of a modern data scientist.I hold a Master’s in Actuarial Science from Columbia University, a Master’s in Industrial Engineering & Operations Research from UC Berkeley, and a B.S. in Actuarial Science, which together ground my work in strong probability, optimization, forecasting, and risk theory.In my current role, I have led cross-functional product and modeling teams, partnering with actuarial, engineering, product, and business leaders to translate analytical research into scalable, real-world solutions. I also train and mentor actuarial and data science analysts, helping teams adopt stronger modeling, coding, and reproducibility practices.I care about building models that work in practice—accurate, fair, interpretable, and maintainable—while developing teams and systems that scale.

Experience

1. Manager, Actuarial Data Scientist

   Optum

   Jan 2022 — Present · US

   Manager, Actuarial / Data Scientist — OptumJan 2022 – Present | United StatesDesigned and deployed machine learning and deep learning models (including LSTM architectures) for utilization forecasting and member behavior analytics across large-scale healthcare datasets. Authored an SOA white paper showcasing the application of LSTMs to telehealth utilization prediction, contributing to industry research and best practices.Developed synthetic data and domain adaptation pipelines to improve generalization across demographic and regional populations.Implemented supervised and unsupervised clustering to improve population segmentation for pricing, product design, and care management.Engineered production-grade ML pipelines in Azure Databricks using Spark and Python, enabling reproducible and scalable deployments.Built modular feature engineering to standardize and accelerate DS workflows across teams.Managed cross-functional product development teams, aligning engineering, actuarial, and business stakeholders around model roadmap & delivery.Trained and mentored actuarial and data science analysts in model development, code quality, version control, evaluation frameworks, and MLOps workflows.Led model monitoring, drift detection, fairness auditing, and lifecycle documentation for governance and regulatory compliance.Named inventor on a UHG patent application (USPTO, patent pending) for a reusable machine learning model framework applied across multiple client implementations.Delivered analytic insights through executive-ready visualizations in Power BI and Tableau.

Education

• Columbia University

  Master's Degree, Actuarial Science

  2014 — 2016

• Instituto Tecnológico Autónomo de México

  Bachelor's Degree, Actuarial Science

  1995 — 2000

• University of California, Berkeley

  Master's Degree, Industrial Engineering and Operation Research

  2002 — 2004

Skills

• Property & Casualty Insurance
• Financial Analysis
• Commercial Insurance
• Microsoft Excel
• Casualty
• Microsoft Office
• Liability
• Financial Risk
• Reinsurance
• Risk Management
• Actuarial Science
• Analysis
• Insurance