Certified Data Scientist

Google Data Analytics Professional Certificate

Google IT Automation Certificate

Bachelor of Technology - BTech

Data Science Problem Setter

• Developed a bias detection service for job descriptions based on the ”masculinity score,” utilizing
semantic similarity and search concepts. Achieved a precision rate of 92% in detecting biased
language.
• Conducted Ad-hoc analysis on Sentence Embeddings (XLMR and BERT) and generated comparative
reports on the performance of XLMR Embeddings for English sentence classification. Demonstrated a
15% increase in accuracy using XLMR Embeddings over BERT.
• Created a Custom NER system for skill tagging and relevant experience extraction from sentences,
leading to a 25% improvement in skill importance detection.
• Performed extensive ad-hoc analysis on Extractive and Abstractive Summarization models,
implementing Pagerank and HF Transformers. Achieved a 30% improvement in summary quality for job descriptions.

Machine Learning Intern

->Worked on Developing Full stack Data Science Applications and Deploying Machine Learning Pipelines on various cloud platforms

Data Science Intern

-> Worked on data collection and data gathering aspects, using web scraping and automation
-> Developed Analytical dashboards on data scraped from various websites,Rms feeds, mobile applications etc.

-> Worked on Exploratory Data Analysis,Supervised and Unsupervised Machine Learning Algorithms
-> Developed Dashboards on various data domains like Sports,Finance etc, using Plotly, Chart.js, d3.js

<p class="leading-6">I have a proven track record of delivering impactful solutions in the field of recommendation systems and natural language processing. I developed multilingual sentence classifiers that achieved an impressive 80% ROC-AUC, significantly enhancing search functionality. Additionally, I created a Named-Entity-Recognition (NER) system with a remarkable precision rate of 85%, specifically tailored for extracting skills from job descriptions. My contributions extended to pioneering an "Apply/Cart-based-recommendations" system that harnessed the power of BERT and neural networks, resulting in a substantial 4.5% increase in click-through rates (CTR). Furthermore, I implemented a cutting-edge "people-also-viewed" recommendation system through Deep Collaborative Filtering, driving a remarkable 5% CTR improvement. In the realm of personalized recommendations, I developed a "browsing-based-recommendations" system leveraging BERT4Rec, which delivered a noteworthy 3.5% CTR boost. My expertise also ex</p>

Product Development Engineer

Machine Learning Engineer @Gartner | Rec-sys | LLM | Mlops | GEN-AI

github

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