Sharad Jain

Data-driven solutions architect, AI/ML engineering expert.

Bengaluru, India

SJ

About

Sharad Jain is an AI founder and seasoned data scientist with a track record of building intelligent systems at scale. As the founder of autoscreen.ai, he architects production-grade conversational AI, leveraging complex technologies like Retrieval-Augmented Generation (RAG) and multi-agent workflows to solve real-world problems. His entrepreneurial drive is backed by extensive experience at companies like Meta and Withjoy, where he led high-impact data science and engineering initiatives.

Education

University of California Davis, Graduate School of Management

2017 - 2018
MS in Business Analytics

University Institute of Technology, Bhopal

2011 - 2015
BS in Mechanical Engineering

Work Experience

autoscreen.ai
Bengaluru

2023 - Present

Founder

Architected and deployed a production-grade, agentic conversational AI for real-time voice, achieving <500ms latency by orchestrating LiveKit, Twilio, and Google's streaming Gemini API. Engineered advanced RAG system to ground text-to-SQL agent in complex database schemas. Designed structured communication backbone for multi-agent workflows with OpenAI function-calling. Developed automated multimodal content pipeline using visual AI (GPT-4.1-mini) for frame-by-frame video analysis, reducing manual content creation efforts by over 80%.

withjoy.com
San Francisco, CA

2020 - 2023

Growth Data Scientist

Architected data-driven growth infrastructure for wedding platform serving 500K+ couples, implementing cohort-based retention models that increased 30-day user retention by 45%. Built experimentation framework with statistical rigor, running 15+ A/B tests quarterly that improved conversion funnel by 28% and reduced CAC by $120. Designed behavioral analytics system using Mixpanel and SQL to identify activation moments, resulting in 2.3x improvement in user onboarding completion rates. Implemented product-led growth loops connecting vendor engagement to organic referrals, driving 35% of new user acquisition through viral mechanisms. Spearheaded cross-platform marketing attribution, achieving 95% accuracy in conversion reporting and 20% YoY channel performance improvement.

Meta (Facebook)
Menlo Park, CA

2018 - 2020

Data Scientist

Implemented MLOps practices for enterprise engineering team, including automated CI/CD pipelines, resulting in 40% faster model deployment and 30% reduction in production issues. Engineered scalable data pipelines using Apache Spark and Airflow, processing 10TB+ daily data, improving data freshness by 50% and model accuracy by 15%. Optimized user onboarding through A/B testing, reducing activation time from 7 days to 2 days and improving retention by 30%.

Autodesk
San Francisco, CA

2017 - 2018

Data Scientist

Implemented machine learning models to predict transient infrastructure failures. Improved prediction accuracy by 15% through feature engineering and model optimization. Built AWS Quicksight dashboard for business insights and interfaced with Data Platform Team in predictive maintenance.

Tata Consultancy Services
Pune, India

2015 - 2017

Data Analyst

Designed and implemented complex ETL mappings using IBM Infosphere DataStage for large-scale data warehousing projects. Performed detailed impact analysis on existing ETL mappings in response to evolving business requirements. Mastered data extraction techniques across multiple data repositories, significantly reducing data retrieval times for analytical reporting.

Skills

Python
SQL
ETL
AWS
Airflow
OpenAI
LangChain
LlamaIndex
Salesforce
MLOps
A/B Testing
Natural Language Processing
Large Language Models
Data Engineering

Open Source Activity

GitHub Contributions

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