Adjunct Lecturer for Mathematics and Statistics and Senior Data Analys

Anna Lizarov

Brooklyn, NY ***********@*****.*** 347-***-****

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Objective

Educator and researcher in Mathematics, Statistics, and Data Science with teaching experience at the undergraduate level and applied research in learning analytics, statistical modeling, and machine learning. Open to teaching mathematics, statistics, data science, and data mining while pursuing research in applied quantitative methods and educational analytics.

Education

M.S., Learning Analytics — Columbia University, New York, NY, 2019 B.A., Forensic Psychology, Minor in Mathematics — John Jay College of Criminal Justice (CUNY), 2017 Teaching Experience

Adjunct Lecturer John Jay College of Criminal Justice (CUNY) — Aug 2024–Present

- Instructor for Principles and Methods of Statistics (STAT 250).

- Designed lesson plans, delivered lectures, and supported 28 students weekly.

- Covered probability, hypothesis testing, regression, and time-series methods.

- Created assignments, graded coursework, and guided statistical reasoning.

- Prepared to extend teaching into Data Science and Applied Data Mining courses. Teaching Assistant Teachers College, Columbia University — Fall 2019

- Supported instruction in Core Methods in Educational Data Mining.

- Assisted with R programming, statistical coding, and data projects.

- Reviewed code, cleaned data, and mentored students. College Assistant (Probability and Statistics I Support) John Jay College of Criminal Justice (CUNY) — 2016–2018

- Assisted students in understanding Probability and Statistics I concepts.

- Provided R and SPSS support for coursework and assignments.

- Conducted data analysis of undergraduate computer science student performance.

- Served as Teaching Assistant for Probability and Statistics I course. Professional Tutor (Math & Science Resource Center) John Jay College of Criminal Justice (CUNY) — 2017–2018

- Tutored statistical and mathematical courses in one-on-one and group settings.

- Assisted students with R and SPSS applications in statistics coursework.

- Supported professional development and student engagement initiatives. Research Experience

Conference Poster LAK2020

Title: How do the Game Level Plateaus Inform the Learning Design Authors: Anna Lizarov, Charles Lang, Kara Carpenter Link to Poster Presentation

Intern Teachley — May 2019–Sep 2019

- Analyzed learning data from digital math games.

- Applied learning analytics and educational data mining to inform design of digital math games. EdLab Services Associate (Development & Research) Teachers College Columbia University — May 2019–Jul 2019

- Conducted analysis and visualization of TC Gottesman Libraries data.

- Researched patron usage behavior and generated reports.

- Collaborated with development team to manage library data infrastructure. Graduate Assistant (Development & Research) Teachers College Columbia University — Feb 2019–May 2019

- Conducted analysis and visualization of TC Gottesman Libraries requests and checkouts.

- Researched patron behavior and produced usage reports.

- Supported development team in building data systems. Awards & Honors

Teachers College Scholarship — Columbia University, May 2018 Dorothy and Solomon Bohigian Operations Research Award — John Jay College of Criminal Justice (CUNY), Mar 2017 Professional Experience (Applied Research)

Senior SEO Analyst Hearst Newspapers — 2025–Present

- Applied statistical methods, NLP, and topic modeling to large-scale data.

- Designed experiments using regression and causal inference frameworks.

- Communicated findings as clear, data-driven insights. Data Analyst Sesame Workshop — 2020–2025

- Conducted regression, clustering, PCA, predictive modeling, and sentiment analysis.

- Designed data pipelines and dashboards to evaluate learning outcomes.

- Collaborated with educators on improving digital learning strategies. Skills

Statistics/Mathematics: Hypothesis testing, regression, PCA, clustering, Bayesian stats, data mining, predictive modeling, machine learning. Programming: R, Python, SQL.

Teaching Tools: Jupyter Notebook, Tableau, Power BI, Google Looker Studio, GitHub. Other: Data wrangling, A/B testing, NLP, performance dashboards. Languages

English (Native), Russian (Native), French (Introductory).

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