Srikanth S is a Data Science Manager at Uber with over 11 years in applied data science and 15 years total experience, specializing in causal inference, recommender systems, interpretable ML, experimentation, forecasting and LLM-driven agentic workflows. He has led cross-functional teams and built production ML systems across gaming, retail, mobility, telecom and CRM—shipping real-time recommenders, contextual bandits, uplift models, and causal optimization that drove measurable revenue and engagement wins. Notable projects include a two-tower recommender with viral-content reranking for games, MILP-based space-allocation and markdown optimization at Walmart, and customer CLV/LTV and pickup-location systems at Ola. An active open-source maintainer (tidypandas, tidypyspark, tidier and others), he blends deep statistical rigor with practical engineering—often building internal packages and experimentation platforms that scale under peak events like IPL. He also places emphasis on model governance and observability, turning complex causal and optimization methods into interpretable, business-adopted solutions.
11 years of coding experience
13 years of employment as a software developer
Master of Science (MSc full time) Applied Mathematics, Master of Science (MSc full time) Applied Mathematics at University of Hyderabad
A grammar of data manipulation for pandas inspired by tidyverse
Contributions:11 releases, 107 commits, 23 PRs in 3 years
tidyversemanipulationdata-analysispythonpolars
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