Nazar Laba
Portland,OR
Summary
Data Science student at Portland State University with hands-on experience building predictive models, engineering data pipelines, and designing analytical dashboards using Python, SQL, and Tableau. Proven ability to work with large, messy real-world datasets — from public business registries to multi-season sports databases — and translate findings into clear, actionable insights. Eager to apply statistical thinking and full-stack analytical skills in a data analyst internship.
Overview
2
2
years of professional experience
Work History
Data Analytics Intern
Trident & Oak Real Estate
Portland, OR
11.2025 - 04.2026
- Cleaned, standardized, and segmented real estate ownership datasets spanning 20 zip codes and 3M+ property records using SQL and Excel, producing analysis-ready tables for stakeholder review.
- Resolved data quality issues — including duplicate ownership entries, inconsistent address formatting, and missing parcel fields — across ~20 separate zip-code-level datasets, improving downstream analysis reliability.
- Wrote SQL queries to filter, join, and aggregate ownership data by geography and classification, enabling ad hoc analysis requests to be fulfilled in minutes rather than hours.
- Built a Tableau dashboard consolidating key investment signals — including ownership concentration, market activity, and price trends — across zip codes, directly informing the team's prioritization of 4 high-potential markets for deeper due diligence.
- Delivered segmented datasets and summary findings to 13 stakeholders, supporting active investment research and translating raw public data into actionable business intelligence.
Sales Associate
Nike Company Store
Portland, OR
06.2024 - 10.2024
- Served [X]+ customers daily in a high-volume retail environment, consistently meeting sales floor productivity expectations.
- Tracked and organized inventory across product categories, maintaining stock accuracy and floor presentation standards.
Education
Bachelor of Science - Data Science
Portland State University
01.2027
Transfer Coursework - Computer Science
Portland Community College
Skills
- Python
- Pandas
- NumPy
- Scikit-learn
- SQL
- Tableau
- Excel
- Matplotlib
- Seaborn
- Data Cleaning
- Feature Engineering
- EDA
- Relational Databases
- SQLite
- Firebase
- Jupyter Notebook
- Git/GitHub
Projects
- NBA Performance Modeling, 2024, Python, SQL, scikit-learn, SQLite, Pandas, Built a regression model in Python (scikit-learn) trained on 8+ years of NBA game-level data (2016–present) to predict player performance outcomes., Engineered [X] features — including rolling averages, per-36-minute efficiency ratios, and usage rates — using Pandas, improving model predictive accuracy by [X]%., Designed a multi-table SQLite schema to join and aggregate across player, team, and game-level datasets, enabling flexible cross-season querying.
- Oregon Business Entity Data Analysis, 2024, Python, Pandas, GeoPandas, Matplotlib, Ingested and processed Oregon Secretary of State public business registry data (~[X] records) to surface geographic and industry-level patterns relevant to real estate market activity., Resolved [X]% null-value rate and standardized inconsistent entity type classifications across [X] columns, producing a clean analytical dataset ready for modeling., Identified geographic clustering of active business registrations across Oregon counties, surfacing [key insight — e.g., underserved commercial zones or high-growth corridors].
- QR-Based Data Collection System, 2023, Firebase, JavaScript, Realtime Database, Architected a QR code check-in system backed by Firebase Realtime Database, replacing manual paper-based collection and reducing per-attendee data entry time by ~[X]%., Captured and structured attendance records for [X]+ event participants, enabling real-time reporting and post-event data exports for analysis.
- Sales & Revenue Dashboard Analysis, 2023, SQL, Excel, Tableau, Wrote SQL queries with multi-table JOINs, GROUP BY aggregations, and window functions to extract KPIs — including revenue by segment, customer retention rate, and top-performing SKUs — from [X] transactions., Built a Tableau dashboard tracking [X] metrics across [X] time periods, enabling at-a-glance identification of revenue trends and seasonal demand patterns.
Websites
Coursework
- Machine Learning
- Database Systems & SQL
- Data Wrangling & Visualization
- Statistical Inference
- Algorithms & Data Structures
- Exploratory Data Analysis
Timeline
Data Analytics Intern
Trident & Oak Real Estate
11.2025 - 04.2026
Sales Associate
Nike Company Store
06.2024 - 10.2024
Bachelor of Science - Data Science
Portland State University
Transfer Coursework - Computer Science
Portland Community College