I’m Pavan Naik, a data scientist and Senior Analyst at Annalect (Omnicom). Raised in Bangalore, India, and now based in Redmond, WA, I’ve spent the past decade working across the U.S. and India at the intersection of marketing science, data analytics, and emerging AI. My focus today is on generative AI, attribution modeling, and large-scale analytics pipelines that turn complexity into clarity.

Education & Foundations

My academic journey began with an M.S. in Electrical and Computer Engineering from the University of Illinois at Chicago (2020), where I specialized in machine learning, pattern recognition, and analytics. Building on that foundation, I pursued a Master’s in Data Science at the University of the Cumberlands (Dec 2024) and am now completing a Ph.D. in Data Science at the same institution (expected 2027), with research centered on generative AI and large-scale data systems.

Beyond Work

When I’m not building AI pipelines, I’m usually painting, hiking Pacific Northwest trails with my husky Arya, or experimenting with creative projects that blend storytelling and technology.

Professional Experience

At Annalect, I’ve advanced from analytics into data science, leading projects that bring AI into production at scale. Some highlights include:

GenAI NL2SQL Translator — built a platform that converts natural language into SQL queries, reducing analysis time by 80%.

Clustering Pipeline at Scale — deployed k-means clustering on 630M+ rows and 1,400+ features using BigQuery ML and Vertex AI.

Markov Attribution Models — designed multi-touch attribution models for the U.S. Army recruiting funnel to optimize marketing investments.

GenAI Insights Engine — developed an LLM-powered dashboard that surfaces KPIs like CPA, ROI, and reach in plain English.

I’ve also mentored analysts, led collaborations with engineers, and driven data solutions that balance technical depth with measurable business impact.

Volunteer & Social Impact

I believe data science should also serve communities and research. My volunteer and research contributions include:

  • One Bread Foundation — built Tableau dashboards from engagement and donation data, boosting donor retention by 22%.

  • Coronavirus Visualization Team, Harvard Innovation Labs — clustered global COVID-19 case trajectories across 180+ countries to inform outbreak response.

  • UIC Department of Psychiatry — developed SVM and logistic regression models to identify postpartum depression risks with 46% predictive accuracy, contributing to early intervention research.