Headline

Technical Leader – Generative AI, LLM Orchestration, Vector Search, LangChain, Voice UX | Architecting End-to-End AI Solutions

About

Data Scientist with 14+ years of experience in building AI based solutions, apps and products. Expertise in Generative AI, building AI agents across multiple sectors. Trader by Passion. Building algortihm for trading using technicals and market sentiments. Expertise in insurance, healthcare, fintech, property, lead business, retail, banking and telecom

Location

Bengaluru

AI stack

aistudio

anthropic apis

antigravity

claude code

claude

deepmind

Work experience

Engineering Manager at Google, Sep 2025 - Present · 1 yr 2 mos, Bengaluru, Karnataka, India

Head of Data Science at Lupin Digital Health, Feb 2023 - Sep 2025 · 2 yrs 8 mos, Bengaluru, Karnataka, India, Building AI & ML solution towards digital healhtcare

Solutions Architect AI at Amazon Web Services (AWS), May 2020 - Feb 2023 · 2 yrs 10 mos, Bengaluru, Karnataka

Deputy General Manager at Magicbricks.com, Oct 2017 - May 2020 · 2 yrs 8 mos, Bengaluru, Karnataka, India, Willingness to Pay Model • Built a model which will predict the amount an owner can pay for package owner wants to buy. • Increased conversion rate of process by 120% and average order size by 10%. • Model is implemented using Kafka & Spark (real time streaming). Lead Engine to Sellers (Project Valuation- 10m USD) • Built a model which will create a requirement & availability score. These leads will be passed to sellers such that they can contact buyers directly (basis on their property requirement). • Using the scoring- Availability module accuracy increased from 50% to 75% and requirement module accuracy increased from 18% to 35% Home loan Conversion model using property data (Project Valuation- 5m USD) • Built a data science model which has increased conversion rate from 0.5% to 3% for home loan using only internal property database. • These leads are passed to banks, DSA which can enhance company revenue by 10%-15% Increase average order size & conversion rate for B2C & B2B process • Built Willingness to pay and prioritization model using machine learning algorithm to increase average order size & conversion rate respectively • Current conversion rate has been increased to 16% from 2% and average order size has been increased to 7K from 4.5K • Customer call pickup rate has increased to 72% from 64%

Team Lead- Data Scientist at Seynse Technologies Pvt Ltd, Jan 2016 - Oct 2017 · 1 yr 10 mos, Bengaluru Area, India, Loan Singh • Currently building a alternate credit model using telco-data • Built alternate data credit model using education, company, social, demographics, and financial factors of a borrower for professional certifications, personal loan and telecom payment bank • Built an unsupervised learning model to score 32,000 colleges and 760,000 companies in the Indian market • 0% default rate post usage of model (current disbursal rate>1 crore per month) • This solution was built using unsupervised learning models and is currently being validated against industry benchmarks in real time market PointsWala • Built recommendation engine using demographics, social, consumer preferences such as brand, price, discounts, color and material, collaborative filtering. This predicts best fashion offer for a particular user using aggregated offers from Flipkart, Amazon, Myntra, Jabong and many more. • This solution was built using unsupervised learning models, Neo4j, graph database and theoretical concept of deep learning

Education

BTECH+MTECH, Information Technology, ABV-Indian Institute of Information Technology and Management

Master's degree, Information Technology, ABV-Indian Institute of Information Technology and Management