Russ Zaliznyak

🌐 Technical Website: rzaliznyak-math.github.io/main

Skills

I specialize in A/B testing and simulation — using simulation studies to turn complex statistical methods into practical tools: apps, Python libraries, and interactive analyses built to feel intuitive and effortless. Teaching and mentoring are equally central — I’ve built training programs, led TechTalks, and mentored peers on statistical methods and Python. AI-assisted development has meaningfully raised the pace and quality of everything I ship.

Experience

Principal Data Scientist · Intuit · January 2022 – Present

Trajectory Changing

App Developer: Built production data apps end-to-end
- AlphaBeta Testing App — interactive experimentation portal, 5,000+ views/month
- Simulation Engine — vectorized pipeline to derive optimal experiment stopping thresholds
New Methods: Introduced modern experimentation techniques
- Stopping & Sensitivity — Bayesian early stopping, CUPED, Informed Priors
- Data Quality & Tooling — Always-on SRM detection, custom Python libraries
AI Early Adopter: Integrated LLMs into production Dash apps via Intuit’s GenOS API
- AI Experiment Designer — conversational AI that guides users through A/B test setup, collecting design parameters and updating app state
- Rapid Prototyping — shipped apps using Cursor and Claude
Teacher & Mentor: TechTalks, training programs, peer mentoring, and ongoing Slack support
Centralized Experimentation Platform i: Every experiment across the company — registered, reportable, and accessible to all teams — with results feeding into an executive dashboard and a searchable knowledge base for past learnings and new test ideas.

Staff Data Scientist · Intuit · February 2019 – January 2022

Making A Difference

Deployed Interactive FAQ Site: AB Test Fundamentals, MABs, SPRT
Introduced Sequential Testing & SPRT methods
Plotly Dash Apps: Sample Size Calculator (Fixed/SPRT) + Experiment Analysis Tools
Respected Experimentation Lecturer
Data Engineering & ETL: PySpark jobs to speed up test analysis

Sr. Data Scientist · Intuit · September 2016 – February 2019

Finding A Niche

Prototyped Experimentation Training Program for Data Scientists
Developed Experimentation Playbook & Guides for non-analysts
Launched App Recommendation Model
Built Customer Cash Flow Prediction Model

Sr. Technical Data Analyst · Intuit · September 2013 – September 2016

Learning The Ropes

Deployed logistic models to predict customer churn; paired with AB tests for outreach
Built Tableau Dashboards to automate AB Test Design & Analysis
Exploratory Data Analysis

Education

Santa Clara University — MS, Mathematics · 2010–2013

San Jose State University — BS, Mathematics · 2005–2008

Santa Clara University — BS, Finance · 2003–2005

Selected Writing

Article	Published
AB Testing is an Optimization Problem	Jun 2026
The Winner’s Curse	Jan 2026
Beta vs Binomial Distribution	Dec 2025
Why Switch to Polars	Oct 2025
The Value of Big Swings	Aug 2025
Experiment Design & Analysis with NumPy	Feb 2025
The Power of Data Simulation	Nov 2024

Links

Contact: rzaliznyak@gmail.com

--- title: "Russ Zaliznyak" subtitle: "AB Testing | Dev | Python | Research | Training | AI" toc: true toc-depth: 2 --- <div style="margin-top:-1.2rem; margin-bottom:1.5rem; font-size:0.95rem;">🌐 <strong>Technical Website:</strong> <a href="https://rzaliznyak-math.github.io/main/" target="_blank">rzaliznyak-math.github.io/main</a></div> ## Skills I specialize in A/B testing and simulation — using simulation studies to turn complex statistical methods into practical tools: apps, Python libraries, and interactive analyses built to feel intuitive and effortless. Teaching and mentoring are equally central — I've built training programs, led TechTalks, and mentored peers on statistical methods and Python. AI-assisted development has meaningfully raised the pace and quality of everything I ship. ## Experience ### Principal Data Scientist · Intuit · January 2022 – Present *Trajectory Changing* - **App Developer**: Built production data apps end-to-end - *AlphaBeta Testing App* — interactive experimentation portal, 5,000+ views/month - *Simulation Engine* — vectorized pipeline to derive optimal experiment stopping thresholds - **New Methods**: Introduced modern experimentation techniques - *Stopping & Sensitivity* — Bayesian early stopping, CUPED, Informed Priors - *Data Quality & Tooling* — Always-on SRM detection, custom Python libraries - **AI Early Adopter**: Integrated LLMs into production Dash apps via Intuit's GenOS API - *AI Experiment Designer* — conversational AI that guides users through A/B test setup, collecting design parameters and updating app state - *Rapid Prototyping* — shipped apps using Cursor and Claude - **Teacher & Mentor**: TechTalks, training programs, peer mentoring, and ongoing Slack support - **Centralized Experimentation Platform** <span data-bs-toggle="tooltip" data-bs-placement="top" data-bs-title="Large cross-functional team effort — my contributions include requirements gathering, dashboard prototyping, pipeline specs, and knowledge base design." style="cursor:help; display:inline-flex; align-items:center; justify-content:center; width:17px; height:17px; border-radius:50%; border:1.5px solid #666; color:#666; font-size:0.75rem; font-weight:800; vertical-align:middle; margin-left:3px; position:relative; bottom:3px;">i</span>: Every experiment across the company — registered, reportable, and accessible to all teams — with results feeding into an executive dashboard and a searchable knowledge base for past learnings and new test ideas. ```{=html} <script> document.addEventListener('DOMContentLoaded', function () { var tooltipEls = document.querySelectorAll('[data-bs-toggle="tooltip"]'); tooltipEls.forEach(function (el) { new bootstrap.Tooltip(el); }); }); </script> ``` ### Staff Data Scientist · Intuit · February 2019 – January 2022 *Making A Difference* - Deployed Interactive FAQ Site: AB Test Fundamentals, MABs, SPRT - Introduced Sequential Testing & SPRT methods - Plotly Dash Apps: Sample Size Calculator (Fixed/SPRT) + Experiment Analysis Tools - Respected Experimentation Lecturer - Data Engineering & ETL: PySpark jobs to speed up test analysis ### Sr. Data Scientist · Intuit · September 2016 – February 2019 *Finding A Niche* - Prototyped Experimentation Training Program for Data Scientists - Developed Experimentation Playbook & Guides for non-analysts - Launched App Recommendation Model - Built Customer Cash Flow Prediction Model ### Sr. Technical Data Analyst · Intuit · September 2013 – September 2016 *Learning The Ropes* - Deployed logistic models to predict customer churn; paired with AB tests for outreach - Built Tableau Dashboards to automate AB Test Design & Analysis - Exploratory Data Analysis ## Education **Santa Clara University** — MS, Mathematics · 2010–2013 **San Jose State University** — BS, Mathematics · 2005–2008 **Santa Clara University** — BS, Finance · 2003–2005 ## Selected Writing | Article | Published | |---|---| | [AB Testing is an Optimization Problem](ab-testing/ab-testing-optimization.qmd) | Jun 2026 | | [The Winner's Curse](ab-testing/winners-curse.qmd) | Jan 2026 | | [Beta vs Binomial Distribution](ab-testing/beta-vs-binomial.qmd) | Dec 2025 | | [Why Switch to Polars](python/polars-vs-pandas.qmd) | Oct 2025 | | [The Value of Big Swings](ab-testing/big-swings.qmd) | Aug 2025 | | [Experiment Design & Analysis with NumPy](ab-testing/numpy-experiment-design.qmd) | Feb 2025 | | [The Power of Data Simulation](ab-testing/power-of-simulation.qmd) | Nov 2024 | ## Links - [ITS Webinar: Going Bayes — Shifting Our Testing Methods](https://rzaliznyak-math.github.io){target="_blank"} - [How Intuit Uses Dash Enterprise](https://www.youtube.com/watch?v=IpcTF0UAIVQ){target="_blank"} --- **Contact:** [rzaliznyak@gmail.com](mailto:rzaliznyak@gmail.com)