Chaitanya Vishnu

About Chaitanya Vishnu

I’m a Data Scientist and AI Engineer with 10+ years of experience building scalable, production-grade solutions across healthcare, BFSI, and retail. I specialize in designing end-to-end AI and GenAI systems — from data engineering and model development to secure deployment and monitoring — across cloud platforms like Azure, AWS, and GCP.My core strength lies in turning messy, high-volume data into intelligent products. I’ve built fraud detection engines, clinical risk models, personalized search systems, and LLM-powered automation workflows using tools like LangChain, GPT-4, FAISS, Hugging Face Transformers, Azure ML, and Databricks. I’ve also implemented full MLOps and LLMOps pipelines with CI/CD, model versioning, and real-time monitoring using MLflow, Kubernetes, and Prometheus.Whether it\'s building a semantic search assistant with secure RAG pipelines or deploying real-time scoring APIs in production, I bring deep technical fluency, platform versatility, and a product-focused mindset.Currently expanding my work in GenAI, multimodal models, and responsible AI — while staying grounded in performance, compliance, and business impact.

Experience

1. Data Scientist (Ai Genai)

   Spacepointe Inc

   Oct 2022 — Present · Fremont, CA, US

   As a Data Scientist (AI/GenAI) at SpacePointe, I led the design and deployment of AI solutions that transformed retail and B2B operations across emerging markets, focusing on intelligent automation, GenAI, and real-time analytics.1. Built LLM-based product classification pipelines using GPT-4, LangChain, and FAISS to improve catalog tagging and discovery. Integrated semantic search and GenAI chatbots to streamline seller onboarding.2. Developed recommendation systems with collaborative filtering in PyTorch to personalize product discovery. Implemented demand forecasting models using Prophet and XGBoost, reducing vendor stockouts by 28%.3. Integrated dynamic pricing optimization into SpacePointe’s platform, adjusting product markups based on real-time demand elasticity and sales trends.4. Fine-tuned multilingual transformer models (mBERT, XLM-RoBERTa) to support product search in francophone and anglophone markets, improving cross-border user experience.5. Built robust ETL pipelines using Azure Data Factory, AWS Glue, and Databricks to unify distributed sales, inventory, and logistics data. Processed large datasets with Spark and Delta Lake to enable efficient training and analytics.6. Deployed real-time scoring services with FastAPI and Azure Functions, embedding AI outputs into SpacePointe’s microservices for faster decision-making.7. Designed anomaly detection models using Isolation Forests and Autoencoders to flag irregular activity in transactions and partner behavior.8. Enabled data-driven decisions through Power BI and Looker dashboards, tracking KPIs such as AOV, seller growth, and cart abandonment.9. Collaborated with business teams to define high-impact AI use cases, support roadmap planning, and drive AI literacy through internal workshops.

Education

• PES University

  Bachelor of Engineering - BE, Mechanical Engineering

• University of the Pacific

  Master's degree, Data Science