Sanika T

1. Reviewed 20–50 daily listings in GYG’s AI-flagged compliance queue, resolving policy, pricing, and safety edge cases.

2. Enforced Trust & Safety standards by auditing animal welfare edge cases across supplier inventory.

3. Conducted post-approval sampling audits on passed listings as a final QA check before supplier content went live.

1. Evaluated QA validation frameworks using Python and SQL for AI training data pipelines across 2 enterprise clients (Mercor and Scale AI), maintaining 98%+ accuracy across high-volume operational cycles.

2. Identified and escalated systematic errors in multi-source datasets via root-cause analysis, reducing
downstream rework and improving data pipeline reliability.

1. Analyzed Google Analytics & Shopify data to build a Zapier cart recovery system, boosting CSAT to 4.9/5.

2. Coordinated 4 cross-functional teams to expand retail into 3 metro cities; each reached ₹3L+ monthly revenue in month 1.

3. Designed an online returns system with a continuous feedback loop, reducing monthly return rates by 2%.

1. Managed 20–30 daily tickets, tracked SLAs, handled escalations, and reported weekly/monthly CS team performance.

2. Piloted internal CS automation, cutting manual effort by 30% to shift focus to strategic initiatives.

3. Partnered with Growth on product launches, feeding frontline feedback to align marketing and boost community engagement.

Selected from a pool of 66,000+ candidates worldwide for Stanford’s Code In Place (CS106A), an intensive, 6-week program covering core programming concepts and problem-solving in Python.

Competitive selection; one-week summer school co-funded by DAAD, with a hackathon component.

Activities and societies: Data Science Centre

Completed graduate coursework for a Master of Statistics and Data Science focusing on data management, probability & statistics, linear models, R programming, and Bayesian inference.

Activities and societies: Certificate Programme in Data Science: Basic & Advanced Excel, VBA, R Fundamentals, Statistical Methods

Postgraduate Diploma in Data Science covering data mining, big data analytics, predictive modelling, time series, statistical inference, exploratory data analysis, and programming in R and Python.

Activities and societies: INSPIRE Scholarship Programme recipient

Bachelor of Science in Statistics with coursework in probability theory, calculus, linear algebra, statistical estimation, operations research, ANOVA, and programming in Java and C++.