Core Product Analytics · Quizlet Application
Data Scientist with 4 years in experimentation, product metrics, and behavioral analysis. I turn student behavior data into product decisions that help millions of learners succeed.
01. Why Quizlet
Quizlet serves over 60 million learners and powers more than 2 billion learning interactions every month. What draws me to this role specifically is the intersection of behavioral data and product impact. Every experiment the Core Product Analytics team runs has the potential to change how a student studies, how long they stay engaged, and whether they actually retain what they learned. That is a different kind of stakes from most product analytics roles. I want to work on a dataset that captures real learning behavior at scale and use it to help the product team make decisions that genuinely improve outcomes for students.
02. Core Skills
Designing and analyzing A/B tests from hypothesis to recommendation, measuring lift, and translating results into product decisions.
Funnel analysis, cohort analysis, retention metrics, engagement tracking, and KPI definition for consumer products.
Advanced querying, large dataset analysis, statistical modeling, scikit-learn, Pandas, NumPy.
Presenting complex findings to product, engineering, and design teams in clear, actionable language.
03. Projects
Project 01 · Vue.ai · Data Analyst, Client Analytics · Feb 2021 – Aug 2022 · SQL, Python, Tableau
Enterprise clients were making pricing and personalization decisions based on intuition with no structured way to measure what was actually working or why.
Designed end-to-end A/B experiments across 15+ enterprise clients covering pricing, promotions, and personalization. Defined control and test groups, selected the right statistical tests, measured conversion lift and revenue impact over 3 week windows, and delivered clear recommendations with confidence intervals and effect sizes that stakeholders could act on immediately.
Ran a personalization experiment testing dynamic product recommendations against a static default layout for a mid-market retail client. The test showed a statistically significant 55% lift in conversion and 22% increase in campaign ROI. The result directly changed how the client structured their entire merchandising strategy going forward.
Project 02 · Vue.ai · Vue Mail SaaS Product · Feb 2021 – Aug 2022 · SQL, Tableau
Vue Mail was a live SaaS product used by 50+ enterprise clients with no measurement framework. The product team had no consistent way to track whether the platform was working or whether campaigns were delivering results across clients.
Defined and standardized core KPIs from scratch including open rates, click-through rates, engagement signals, and campaign conversion. Analyzed performance patterns across all clients to identify which product features were driving retention. Found that clients using personalized send-time optimization had significantly higher engagement than those on fixed schedules, which directly influenced the product team's decision to prioritize that feature in the next release cycle.
This work became the foundation for all future product analytics at Vue Mail and gave the team their first reliable, consistent view of platform performance across all 50+ clients.
Project 03 · Rutgers School of Public Health · Data Scientist · Oct 2023 – May 2024 · Python, Snowflake, SQL
A research team was losing survey respondents midway through long questionnaires with no understanding of where or why drop-off was happening, making it impossible to improve completion rates.
Used regression analysis and hypothesis testing to identify the exact questions and survey sections where respondents were abandoning. Found that question complexity, length of individual sections, and lack of progress indicators were the three primary drivers of drop-off. Translated findings into specific redesign recommendations for the research team.
Identifying where students disengage and why is one of the most valuable things a data scientist can do for a learning product. The methodology I used here — isolating behavioral signals, testing hypotheses about friction points, and delivering specific actionable recommendations — is exactly how I would approach student engagement and retention analysis on Quizlet's platform.
04. Experience
Vue.ai
Data Analyst, Client and Product Analytics
2021 to 2022 · Chennai, India
Workforce Professionals Training Institute
Data Infrastructure Engineer
2024 to Present · New York, USA
Rutgers School of Public Health
Data Scientist
2023 to 2024 · New Brunswick, USA
Hirestar.io
Analytics Engineer
2020 · Hyderabad, India
05. Contact
I bring 4 years of hands-on experience running experiments, defining product metrics, and translating behavioral data into decisions that move products forward. Every project in this portfolio is real work with real outcomes. I would love to bring that same rigor to Quizlet's Core Product Analytics team.
Rutgers University
MS Computer Science
Courses: Machine Learning, BI and Visual Analytics, NLP, Advanced AI
3.96 / 4.00
Certifications
Built for Quizlet · Darshan Senthil · www.darshansenthil.com