Himamshu Ravi

Product Manager

Bengaluru, Karnataka, India9 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Developed a GenAI analytics chatbot reducing insight generation time.
Drove $16.5M in incremental sales through data-driven strategies.
Led a team to achieve over 90% automation in document classification.

Stackforce AI infers this person is a Data Science and Machine Learning expert in the Retail and Healthcare sectors.

Contact

Skills

Core Skills

Data ScienceMachine LearningNatural Language Processing (nlp)

Other Skills

Analog Circuit DesignBootstrapCC++Cascading Style Sheets (CSS)CommunicationDeep LearningElasticSearchHTML5KibanaLogic DesignMicrosoft ExcelMicrosoft OfficePythonR

About

I love solving problems and fortunately for me, I am in the right profession for it.

Experience

Walmart global tech india

Senior Product Analyst

Aug 2022 – Present · 3 yrs 7 mos · Bengaluru, Karnataka, India

Built and deployed RAPTOR, a GenAI, agent-first analytics chatbot for Perfect Order diagnostics, combining Conversation, EDA, Forecast, and Root-Cause in one UI. Accelerated insight-generating timeline from hours to minutes, freeing up ~2.5k hours of analytics bandwidth
Claims agent - Claims agent : building an agent to analyze high-volume claims, Uncover patterns and validate root causes and Accelerate targeted intervention deployment
Created a re-usable / deployable agentic architecure for a chatbot that can do data anlytics, forecasting and conversational tasks (email writing, summarization)
Improved in-stock rates by 4% and minimized potential sales loss at fulfillment centers by leveraging data-driven insights, visualizations, and prioritization of dwell time and trailer unloading.
Enhanced truck ETA accuracy by 15% through collaboration with SDEs, business teams, and vendors; developed a framework to measure and analyze accuracy, driving continuous improvements.
Drove $16.5M in incremental sales within one year by partnering with the product team to introduce in-transit inventory for e-commerce; built dashboards to track sales and optimize in-stock metrics.
Accelerated inventory processing by 14% and reduced dwell time at the Import Distribution Center through a detailed analysis of inbound and outbound processes, improving overall supply chain efficiency.

PythonNatural Language Processing (NLP)Machine LearningData ScienceSQLElasticSearch

Amazon

Business Analyst

Oct 2021 – Jul 2022 · 9 mos · Bengaluru, Karnataka, India

Mu sigma inc.

Data Scientist

Aug 2018 – Oct 2021 · 3 yrs 2 mos · Bengaluru Area, India

Worked with the Data Sciences team of fortune 50 Pharmaceutical company to effectively solve the Key Opinion Leaders identification problem using metrics like Publications, Clinical Trials participation and Prescription pattern. The solution was built using Machine learning algorithms like Clustering and Random Forest. Created a scalable framework to expand the solution to over 500 markets.
Ideated and executed a Medical Context Engine prototype empowered by Natural Language processing and Deep Learning in order to build a cross-language search strategy generator eliminating the need for intervention by Subject Matter Experts.
Built a comprehensive Network Graph of physicians in order to understand influence of a physicians over a community and interactions between HCPs to enable business decisions like recruitment of HCPs in speaker programs, Site selection for Clinical trials and Identifying specialists to help manufacturers during drug development
Designed a prototype that helps clinical researchers facilitate faster research by providing accurate context based search results and extractive summaries. The prototype is built on Natural language processing based word vectors to support context searching and page rank for text ranking to extract summaries from the paper. The prototype produced 95% more accurate results than standard solution for clinical research.
Led a team of data scientists in collaboration with the business teams of one of Australia’s largest Banking and finance companies to perform document classification for CTP claim documents. Built 2 classification frameworks to identify new claims and type of claim document submitted. Successfully achieved over 90% automation and accuracy scores across both the models using lightgbm classifier.

Machine LearningNatural Language Processing (NLP)Data Science