Dinara Zhorabek
Dinara Zhorabek
Data Analyst & ML Engineer
Boston University — M.S. Applied Business Analytics (’26)
Python · SQL · ML · Dashboards · Data Pipelines

Hi, I’m Dinara.

Data engineer and analyst with 3 years of experience building production pipelines, AI-powered platforms, and data governance systems across finance, healthcare, and labor markets.

I’m finishing my Master’s in Applied Business Analytics at Boston University, with a B.S. in Information and Communication Technology from Kazakh-British Technical University. My background spans full-stack engineering and data systems, and my recent work includes building LangChain-powered analytics platforms, end-to-end ETL pipelines over millions of records, and AI-assisted workflows deployed in production.

I’m particularly interested in roles where data infrastructure and applied AI intersect — where the pipelines I build directly shape decisions people can act on.

Outside of work, I enjoy traveling, building disciplined habits, and baking sweets.

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Projects

Inertia Trading – Boeing & S&P 500

Analyzing short-term trading behavior in Boeing using rule-based strategies, machine learning classification, and clustering, benchmarked against the S&P 500. Includes day trading simulations and cross-stock behavioral analysis.

Words, Locations, and Prices

Airbnb analysis in Copenhagen exploring neighborhood patterns, listing language, and pricing signals with interactive visuals.

Job Market Analysis 2024

Conducted a comprehensive analysis of the 2024 U.S. job market by integrating Lightcast job-posting data with FRED macroeconomic indicators and applying machine learning, NLP, and statistical exploration to model hiring trends, skill demand, gender disparities, and regional wage patterns, publishing insights in an interactive Quarto website.

You Like This Song…But Will George Like It?

User behavior classification with Spotify streaming data to predict preference patterns and key drivers.

Clustering Pokémon

A hierarchical approach to character grouping using clustering methods and similarity analysis.

Vortex Sentiment Adaptive Volatility (VSAV)

Hackathon project building a sentiment-aware volatility strategy with backtests and interactive reporting.

Say My Name

Unpacking emotion and language in Breaking Bad using R text mining and sentiment analysis.

Complaint Classifier

Naïve Bayes model to classify consumer complaints and predict dispute outcomes.

Market Basket Insights

Association rule mining to discover product co-purchase patterns and actionable bundles.

Skating through Data

Forecasting hockey player salaries using statistical analysis and machine learning methods.

Console to Category

Predicting video game sales outcomes using classification trees and model comparison.

Voices of the City

Analyzing Vancouver’s 311 service requests to uncover trends, hotspots, and operational insights.

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