Turning raw data into decisions worth trusting.

Data Analyst — Northbrook, IL

I turn messy data into clear, decision-ready analysis using Python, SQL, Power BI, and statistical modeling — with hands-on ETL and cloud experience in Databricks and AWS, grounded in a background in sales and CRM data.

See the Portfolio Download resume

Foundation

The base layer — the languages, tools, and coursework that everything downstream gets built on.

Languages & analysis

Python
SQL
R
Statistical analysis
Machine learning
Object-Oriented Programming (OOP)
Statistical modeling
Applied machine learning
Supervised learning
Logistic regression
Decision tree learning
Probability & statistics
Data cleansing
ggplot2
R Markdown

Data engineering & cloud

Databricks
Apache Spark
PySpark
Delta Lake
Lakehouse architecture
Unity Catalog
Databricks CLI
ETL pipelines (medallion architecture)
Data pipelines
Data modeling
Database design
AWS (S3, EC2)
AWS Glue
Amazon DynamoDB
Amazon CloudWatch
IAM
Serverless computing
Cloud security
BigQuery

Visualization & reporting

Power BI
Tableau
Excel (Pivot Tables, VLOOKUP/XLOOKUP)
Google Sheets
KPI reporting
Dashboard design
Interactive data visualization
Business intelligence
Data-driven decision-making

Machine learning & emerging tech

Federated learning
PyTorch
TensorFlow
Flower
Homomorphic encryption

Business tools

Salesforce CRM
Business analysis
Workflow management
Data ethics
Cross-functional collaboration
Stakeholder communication
Bilingual — English, Russian

Certifications

Education

Lake Forest College

B.A. Communication — Minor: Legal Studies & Philosophy, 2019
Oakton Community College

Associate in Liberal Arts, 2016

Employment History

Nov 2024 – Present

Analytics and Development Intern

GCA Research & Consulting Services, Inc. — Remote

Support early-stage development of a proprietary health and wellness application in a confidential capacity, while learning and applying data lake architecture concepts, including how raw application data is ingested, stored, and organized for analysis.

Aug 2023 – Mar 2024

Sales Associate

Sleep Number — Deerfield, IL

Sold smart beds and sleep products through consultative, needs-based showroom conversations. Managed customer follow-ups in Indigo CRM to keep prospects engaged through to purchase, and tracked sales against shifting KPI targets in Power BI to adjust the daily selling approach.

Apr 2021 – Feb 2023

Inside Sales Representative

Quill (Staples Inc.) — Lincolnshire, IL

Ran outbound reactivation calls to customers inactive 4+ months, using coupon offers to win back accounts, and reviewed Salesforce purchase history before each call to anticipate needs and tailor recommendations. Sold Quill Plus Blue paid memberships by connecting membership benefits to each customer's ordering patterns. Designed a dynamic dashboard monitoring real-time call duration, raising daily talk time from the 3 hr 45 min minimum to ~5 hours, a 33% increase.

Feb 2019 – May 2019

Marketing Intern

Kaplan Law Offices — Northbrook, IL

Wrote client success-story articles for the firm's website, optimizing content with targeted SEO keywords to improve search visibility, and designed holiday-themed campaign flyers to engage the local community as low-cost advertising for the firm.

May 2018 – Aug 2018

Legal Intern

Bikbova Law Offices — Northbrook, IL

Researched and compiled country conditions reports, synthesizing geopolitical and human rights sources into evidence, and organized key information from legal documents and client interviews into structured case files for attorney review.

Jun 2013 – Sep 2020

Event Setup & Décor Technician

Neky Design — Northbrook, IL

Loaded, transported, and installed décor on-site, including pipe-and-drape, LED uplighting, and vinyl dance floors, completing setups and teardowns within fixed event and venue time windows.

Portfolio

The refined output — work built and shipped end to end, from raw data to a finding someone could act on.

Rent Responsibly

2026

A location-aware rental affordability tool: combines commute isochrones, live rental listings, and full household financial modeling (tax, debt, expenses, fuel) to evaluate whether a move is sustainable under single-income and co-signing scenarios.

Python
Pandas / GeoPandas
Mapbox API
Geospatial analysis
Financial modeling

View on GitHub

Relocation Feasibility Analysis

2026

Models income, housing costs, debt, and living expenses against real government data — HUD housing figures and Tax Foundation tax data — to answer a concrete question: is a specific relocation actually affordable, not just possible.

Python
Polars
HUD data
Tax Foundation data

View on GitHub

Monte Carlo Job Offer Comparison

2026

Runs a 50,000-trial Monte Carlo simulation to compare compensation structures across job offers, turning uncertain, volume-based commission math into a distribution of likely outcomes rather than a single guess.

Python
NumPy
Monte Carlo simulation

View on GitHub

Clipboard Health Case Study

2025

Analyzed CMS Payroll-Based Journal staffing data and provider records across 14,000+ U.S. nursing homes to identify staffing cost inefficiencies, model resource demand, and deliver strategic recommendations to sales leadership.

Python
Machine learning
CMS PBJ data

View Presentation

Google Data Analytics Capstone

2025

Integrated Divvy bike-share ridership data with hourly weather data to uncover behavioral trends and develop data-driven recommendations for growing annual membership enrollment.

R
RStudio

View Presentation

Customer Call-Time Optimization Dashboard

2022

Designed a dynamic Google Sheets dashboard at Quill that monitors real-time call duration in 15-minute segments and recalculates the pace needed to hit the daily talk-time goal. Using it raised my daily talk time from the 3 hr 45 min minimum to ~5 hours, a 33% increase.

Google Sheets
Dashboard design

View Dashboard Get Your Own Copy

How to use this dashboard

Make your own copy of the sheet, then duplicate the "Call Time Planner" tab. Do all of your daily edits on the Copy of Call Time Planner tab — this keeps the original tab clean and makes resetting for the next day easy.
If your shift starts at a different time, edit cell G2 under the TOD column.
Set your goal in cell O8 — clicking it reveals a dropdown. Selecting 3:45:00 sets an average call-time target of 0:08:02 per 15-minute segment; selecting 4:30:00 raises that target to 0:09:39.
If you're participating in a Flex Time program (working a bit extra Mon–Thu to leave early on Friday), add Flex Time starting with the first item in the list, adding more as your policy permits. Each addition lowers your required goal per 15-minute segment.
If you're leaving early, start unchecking the L column from the bottom. Also make sure no Flex Time is checked.
Block out breaks, lunch, and meetings — those segments highlight in yellow to mark their start and end.
Throughout the day, once a 15-minute segment is complete, edit that row's Adjusted cell with your actual call time. Delete the existing contents and type your time with no equals sign, in 00:00:00 format (e.g. 00:05:00). The next row automatically recalculates the call-time goal needed to stay on track.