About Me
I’m Manuela Lozano, a UCLA graduate in Statistics & Data Science and Economics, currently preparing to begin my M.S. in Statistics at the University of Washington.
I like building things that make data useful. My work sits at the intersection of machine learning, analytics, business intelligence, and applied AI — from forecasting pipelines and dashboards to LLM-powered tools and statistical modeling projects.
What drives me most is not just building technically correct models, but turning messy real-world data into something people can actually use to make better decisions.
My Journey
I originally became interested in economics because I enjoyed understanding how people make decisions. As I took more statistics courses at UCLA, I realized that data could answer those questions in a rigorous, quantitative way.
That curiosity eventually led me toward machine learning and AI. Since then, I’ve built forecasting pipelines at AWS, developed a retrieval-augmented AI assistant for investment education, and worked on projects across healthcare, finance, marketing, econometrics, and NLP.
Today, I’m most interested in building data products that combine statistical modeling, software engineering, and practical business impact.
Career Timeline
2022
Started at UCLA
Began studying Statistics & Data Science and Economics.
2024
Data Analyst Intern · IDT
Worked on predictive analytics, SQL workflows, and dashboards.
2024–2026
Data Analyst / Data Scientist · Insights Investment WM
Built predictive models and an AI-powered investment education assistant.
2025
Business Intelligence Engineer Intern · AWS
Built forecasting pipelines, dashboards, and analytics workflows.
2026
Graduated from UCLA
Completed dual degree in Statistics & Data Science and Economics.
2026
Incoming M.S. Statistics Student · University of Washington
Preparing to deepen my work in statistical modeling and applied data science.
What I Work On
Machine Learning & Statistics
Predictive modeling, classification, regression, forecasting, NLP, experimental design, and applied econometrics.
AI Applications
LLM tools, RAG systems, vector search, prompt engineering, and AI products that support real users.
Analytics & Business Intelligence
SQL workflows, dashboards, data visualization, reporting automation, and translating analysis into decisions.
Skills & Tools
Languages
- Python
- R
- SQL
- HTML/CSS
Data & ML
- pandas / NumPy
- scikit-learn
- CatBoost
- tidyverse
- ggplot2
- Tableau
- QuickSight
- Quarto
Methods
- Regression
- Classification
- Forecasting
- Time Series
- NLP
- Panel Data
- A/B Testing
- RAG / LLM Agents
Beyond the Classroom
At UCLA, I’ve been involved in communities that taught me how to lead, communicate, and work across different groups. As a Resident Assistant, I supported students and designed community programming. Through the Latin American Student Organization, I worked on mentorship, cultural engagement, and student outreach. With Engineers Without Borders, I supported internal operations and team coordination.
These experiences shaped how I work: I care about clarity, collaboration, and building things that are useful to the people around me.
What I’m Looking For
I’m interested in roles across Data Science, Machine Learning, Analytics Engineering, Business Intelligence, and Applied AI.
I’m especially excited by teams building data-driven products, AI tools, or analytical systems where strong statistical thinking and practical execution both matter.