Anshul Kumar Gupta

o Architected Strategic Frameworks - Designed and scaled foundational frameworks for AI evaluation, Competition research, and AI agent development. o Led AI Product Development - Drove the end-to-end lifecycle of key AI/ML features, leading VWO Copilot from initial POC to full production launch. o Owned Core Statistical R&D - Drove the statistical overhaul of platform's A/B test reporting; Derived the foundational mathematics for Bayesian Reporting and MAB. o Product Strategy, User Research & Hiring - Contributed to the long-term Analytics & AI product strategy, validated roadmaps through customer interviews, and provided key support in senior data science hiring.

- Built a novel approach to estimate sample size in Bayesian A/B test. link - https://engineering.wingify.com/posts/maths-behind-bayesian-duration-calculator/ - Built an approach to dynamically allocate dynamic traffic in A/B test through multi-armed bandits. https://help.vwo.com/hc/en-us/articles/900003845666-Understanding-the-Working-of-Multi-Armed-Bandit-in-VWO

- Built an ML project to optimize certain rule based fraud detection scenarios by doing customer profiling and cluster based thresholds computation in Python. - Was involved in creating an APM tool to get performance and business metrics from client’s environment to cloud. - Given POC of several anomaly detection algorithms to Product Managers and Software Developers. - Currently working on a Next Best Product prediction model for a client.

Built end to end churn model for a major Telecom company.

- Build ETL pipelines using kafka, HDFS, Hive, Oozie and SQL Warehouse on Azure. - Build monitoring and anomaly detection system using Collectd, StastD, Carbon and Grafana. - Involved in developing Predictive Models to determine users’ likeliness of uninstalling an App in Python. - Developed Case Studies on User behavior towards a Mobile application using R and D3.js. - Build a search system on Redis. - Developed automated reporting system for weekly and monthly reports in R. Tools- AzureML, ETL Pipelines, Realtime Monitoring and Anomaly Detection System, D3.js, Graphite Hadoop, Hive, Oozie, Sqoop, Azure SQL Warehouse

Developed algorithms - to determine Social Influence Index of Brands on Social Media - to determine how likely a post is boosted on Facebook.

Was involved in performing case study for Ajay Ohri's book "Python for R users" Internship work- https://datascienceinsider.wordpress.com/2016/02/08/internship-experience-of-working-in-decisionstats/

Developed Natural Language Algorithms for scoring, clustering and correcting Subject Case Matters.