Jan 2026 – Present · 5 mos · Virginia, United States · Remote

Aug 2025 – Present · 10 mos · McLean, VA · Hybrid

Dec 2024 – Aug 2025 · 8 mos · United States · Remote

• Shaped the product strategy for JiraBot, identifying developer productivity gaps, validating requirements with stakeholders, and driving execution of an LLM-powered assistant that streamlined task management in Slack.
• Defined vision, architecture, and roadmap for Knowledge AI — a GenAI-enabled enterprise search platform — resulting in patent recognition and company-wide adoption.
• Conducted root-cause analysis and user interviews to redesign UAR workflows, leading to a 3× reduction in handling time (90 → 30 min) and $2M+ annual savings.

Aug 2024 – Present · 1 yr 10 mos

Dec 2023 – Dec 2024 · 1 yr · United States · Remote

• Defined use case, product requirements, and success metrics for a LangGraph-powered multi-agent call intelligence platform, reducing manual review by 85%.
• Led the development of a call summarization application using GPT-3.5 Turbo on AWS Sagemaker, enhancing transcript analysis.
• Prioritized roadmap, managed cross-functional delivery, and aligned engineering, product, and ops teams for GenAI initiatives impacting multiple business units.
• Spearheaded LoRA fine-tuning initiatives, achieving a 25% improvement in model accuracy and a 70% reduction in training time.
• Ran end-to-end product discovery and PoC evaluation for a video-to-text chatbot, validating feasibility and improving extraction workflows for customers.

Aug 2022 – Dec 2023 · 1 yr 4 mos · Dallas, Texas, United States · Hybrid

• · Implemented Multi-Modal Text Classification model using BERT to predict Auto-Subrogation claims on 1M claim notes.
• · Trained and deployed text classifiers with Word Embeddings, LSTM, BERT using TensorFlow, Keras on Walmart’s ML Element Platform.
• Led internal enablement and adoption strategy for Walmart’s NLP/LLM initiatives, improving model performance and developer skillsets across multiple teams.
• Defined team priorities, coordinated cross-functional requirements, and drove delivery of end-to-end ML products improving claims prediction accuracy.
• · Formulated Custom NER Model to extract Provider Details from Walmart Claims Notes data of 100k records using NLP and Text Mining.

Oct 2021 – Jan 2022 · 3 mos · Tempe, Arizona, United States · Hybrid

• • Developed Aspect-level Opinion Mining Model on Twitter Text Covid Data on 1.5 million Tweets utilising Google’s BERT with 75% precision.

Sep 2021 – Apr 2022 · 7 mos · Tempe, Arizona, United States

• Developed a Multi-label text classification model from scratch by classifying 30k adidas product reviews using Google BERT and Huggingface Transformer.
• Scrapped 30k Customer Reviews for Adidas products from Reddit using PRAW and classified reviews and non-reviews.
• Pre-processed 30k records using NLTK and Spacy and performed EDA using interactive Jupyter notebooks using Plotly, Pandas, and Numpy.

Feb 2018 – Aug 2021 · 3 yrs 6 mos · Noida, Uttar Pradesh, India

• Created an R shiny application using Text Mining and Machine learning techniques to accurately auto-generate a summary of bio-statistical analysis that reduced the 2-week equivalent of man-hours of time.
• Analysed and transformed data leveraging tools such as PostgreSQL and Excel to develop and execute SQL scripts to create data extracts and reports.
• Developed R Application using Text Mining and NLP to standardize unstructured data, saving 80% of
• manual intervention.
• Created a custom R shiny application for a data-driven decision tree with 100 features.
• Made data-driven recommendations to optimize the overall data management performance by 15%.
• Performed various data analytics in SQL and Python by deploying statistical and predictive models.
• Automated the process of validating the document abstraction process.
• Used NLP(Custom NER) to extract entities like Drug Names, Adverse Events, Generic Drugs, Number of Patients etc.
• Implemented Statistical tests (correlation, ChiSquare) and Machine learning(Logistic Regression, Random Forest, RFE, PI) tool to build the solution and integrated with Power BI for dashboard and visualization.
• Used Life Science Analytics framework of clinical SAS to create Analysis Data Models (ADaM's) as
• per CDISC standards for Phase 2 and 3 clinical trials.
• Based on the respective ADaM's created tables, listings, and figures for Phase 2 and 3 reproductive trials on SAS 9 Enterprise Guide.
• Assisted 3 senior analysts in analyzing & interpreting collected data.
• Rendered insights & generated analytical reports with recommendations to enable strategic planning by management.

Aug 2014 – Nov 2017 · 3 yrs 3 mos · Noida · On-site

• Collected, studied, and interpreted large datasets; conducted reports; performed accurate, successful
• data management from Sybase Database.
• Analyzed and transformed data utilizing tools like PostgreSQL and Excel to develop and execute SQL scripts to build data extracts and reports in Tableau.
• Extensively implemented SAS macros in automating the quarterly reporting of customer enrollments in
• the insurance coverages.
• Conducted Multiple Linear Regression models on Python to predict the number of enrolments in insurance coverages in future enrolment periods achieving a 15% more accurate prediction of performance than previous years.
• Segmented Customers using k-Means and k-Prototype that have similar demand characteristics predicting customer’s likelihood of renewing policies.
• Developed Key Performance Indicators (KPI) on Tableau dashboards on the number of enrolments in insurance coverages over time.
• Implemented PL/SQL procedures to automate the manual CRUD operations, thereby reducing 90% of manual work done in updating DB tables.
• Designed, Developed, Tested and Maintained Tableau Dashboard and stories based on user
• requirements.