Seasoned professional who combines data, AI, and product thinking: rigorous analysis, AI systems, product-minded execution, and business outcomes.
Data
SQL, ML, data warehouses, dashboards, experimentation.AI
RAG, agentic workflows, LLM apps, fine-tuning, automation.Product
PRDs, success metrics, prioritization trade-offs, user empathy.
Enterprise contract intelligence system for grounded answers over supplier agreements.
Manual contract review made liability discovery slow, inconsistent, and hard to audit.
SQL filters, vector retrieval, query rewriting, reranking, and cited answer generation.
$300M+ liability visibility with source-backed clauses for executive decisions.
Agentic RevOps workflow that turns Reddit and search signals into qualified GTM content.
GTM teams lose time moving between scraping, scoring, drafting, and manual QA.
Specialized agents handle ingest, grading, RAG validation, generation, and approval.
Designed to lift pass rate toward 85% while reducing hallucination risk.
End-to-end e-commerce recommendation pipeline predicting probability of purchase.
E-commerce teams need scalable recommendations from noisy click, view, and purchase events.
Bronze, Silver, and Gold Delta layers feed PySpark features, candidate generation, and an XGBoost ranker.
MLflow registry, REST serving, offline metrics, cold-start handling, and drift monitoring.
Data science lab for turning A/B tests into product growth decisions.
Teams need evidence for ship, hold, or iterate decisions beyond vanity metrics.
Power analysis, funnel SQL, uplift estimates, confidence intervals, and guardrails.
Decision readout connects statistical lift to revenue, retention, and risk metrics.
AI product tool that converts user reviews into PRD-ready roadmap inputs.
Review data is noisy and difficult to translate into clear product priorities.
Topic modeling, sentiment signals, AI synthesis, PRD sections, and metric framing.
Turns customer feedback into prioritized features, goals, and success metrics.
Production ML pipeline for predicting EV charging station surge risk.
Operators need early warnings before demand spikes overload stations and routes.
Raw data prep, feature engineering, validation gates, API serving, and drift checks.
Deployable FastAPI service with risk scores, recommendations, and monitoring metrics.
Hybrid retrieval with sub-query decomposition, BM25+vector fusion, and BGE re-ranking. Built to surface facts without hallucinating on high-stakes decisions.
Stateful multi-agent pipelines with typed handoffs, human-in-the-loop checkpoints, and graceful fallbacks.
Review mining, structured synthesis, prioritization, PRD creation, and success metrics tied to real user problems.
Feature engineering, validation gates, model serving, monitoring, and deployment artifacts for production-minded ML.
Power analysis, confidence intervals, funnel metrics, guardrails, and decision readouts for product growth.
ETL orchestration, dimensional modeling, data quality checks, KPI dashboards, and executive reporting.
Machine learning, unstructured data analytics, transformers, NLP, agentic AI, computer vision, AI business strategy, data governance, SQL, data warehousing
AI products, RAG contract intelligence, supplier workflows, $300M+ liability impact, business metrics, stakeholder delivery
SQL, Tableau, Snowflake, predictive analytics, machine learning, dashboards, KPI reporting, executive decision systems
Open To AI, Data & Product Roles
Targeting AI engineer, data/ML, analytics, and AI product roles where RAG, agents, ML systems, experimentation, SQL, dashboards, and business metrics all matter.
Contact Mokshith →