Hovanes Gasparian

Los Angeles, CA · (323) 540-4686 · hovanes 'at' berkeley 'dot' edu

My name is pronounced Ho-vawn-es, but most just call me Hov (yes, like Jay-Z). In my past life I worked in politics, at the federal as well as state levels. In my reincarnated past life, I was an aspiring academic. Now, I’m a data scientist! Regardless of how many lives I have left, I will always love helping others, analyzing data, and having fun.


  • Data Analysis
  • Data Visualization
  • Statistical Modeling
  • Machine Learning
  • Natural Language Processing (e.g. VADER, Google Cloud NLP).

Some of my favorite Python libraries and tools:

  • Pandas
  • NumPy
  • SciKit-Learn
  • SciPy
  • StatsModels

Some of my favorite tools for Data Visualization:

  • Matplotlib
  • Seaborn
  • Plotly


Machine Learning Engineer


I work on improving and expanding VIZIO's recommender systems, and personalization efforts more broadly. From data engineering in AWS, to MLOps in Databricks, I navigate complex big data pipelines and am responsible for end-to-end solutions that enhance the user experience of millions of customers.

March 2021 - Present

Data Science Instructor - Local Lead

General Assembly

I taught students Python for Data Science (primarily in Jupyter Lab/Notebooks). Topics range from various machine learning models, statistical methods, and algorithms for both regression and classification problems, as well as unsupervised learning methods like clustering and recommender systems. I guide students through 3 months of a very rigorous data science curriculum, including 5 projects and a final capstone for their portfolios.

December 2019 - March 2021

Data Scientist


I used a variety of tools to conduct data analyses for officer performance and agency insights such as SQL (Metabase and Valentina Studio) and Python (Jupyter Lab) I also engaged in natural language processing (NLP) using Google’s Natural Language API for sentiment and entity analyses on unstructured data (e.g. constituent feedback and survey responses), in addition to VADER. I developed numerous dashboards in Metabase for dynamic visualizations that automated recurring analytics (e.g. monthly and quarterly statistics by agency).

June 2019 - August 2019

Junior Data Scientist


I conducted various policy analyses and developed reports for presentation to Members of Armenian Parliament and the Economic Development Committee. I also collaborated with the rest of data science team to build our in-house data cluster, to speed up our data collection, cleaning, and analyses.

November 2018 - February 2019


University of California - Berkeley

Bachelor of Arts
Major: Political Economy of Industrialized Societies

Minor: City and Regional Planning

August 2005 - May 2009

University of Southern California

Master of Public Policy

Specialization: Education Policy

GPA: 3.8

August 2012 - May 2014


Programming Languages & Tools
  • Jupyter Notebooks & Jupyter Lab
  • Statistical Modeling & Machine Learning
  • Cross Functional Teams
  • Reporting to technical & non-technical audiences

Personal Interests

Apart from being a data scientist, I enjoy most of my time being outdoors. In the pre-pandemic era, I was an avid soccer player. I enjoyed mountain biking, snowboarding, and playing tennis.

In the post-pandemic era, my time gaming and Netflixing has increased exponentially. The Witcher and Dark are two of my favorite shows of all time. The Legend of Zelda: Breath of the Wild replaced Ocarina of Time as my favorite game of all time.

Awards & Certifications

  • General Assembly - Data Science Certification
  • Robert P. Biller Award for Best Policy Analysis
  • 1st Place - Policy Solutions Challenge USC
  • 2nd Place - Policy Solutions Challenge USA
  • 2nd Place - USC Price Nonprofit Case Challenge