Hi there , I am Yash , I am a Master's student in Data Science at Worcester Polytechnic Institute (WPI) also AI Research Assistant at (WPI) with a passion for data science and AI/ML . I have done my Bachelor's in Computer Science and Engineering, I bring a blend of academic excellence and practical experience to the table.
In my current role as AI Research Assistant at WPI and in collaboration with Availity clinical Solutions ( A Healthcare Tech company ) we integrate AI and machine Learning strategies to upcycle the data for Healthcare Industries such as HL7 international and FHIR.
Previously, as a Data Scientist at TATA Consultancy Services (TCS), I worked on developing and deploying AI models that boosted sell-through rates by 19% and increased sales revenue by 25%.
My experience also includes deploying ELK Stack dashboards at Xoriant, enhancing data analysis and Visualizations , I also recieved pre-placement offer from Xoriant to work their as Associate Software Engineer
I specialize in Risk and Financial analysis , Advanced Data Visualization for better understanding in exploring complex data sets using Tableau and Power BI , Natural Language processing Projects , and integrating Deep learning models such as GAN's (Generative Adversarial Networks) and Diffusion models which are the backbone of ChatGPT from OpenAI.
Unlike others - I Appreciate small talks , it helps in learning from people's various Experiences , I am a life-long learner , i believe in pushing myself every single day. Let's connect to discuss more !.
● Analyzed 25+ healthcare databases to identify trends and data issues using Python, Tableau.
● Reduced deployment time by 2 weeks by developing and deploying Generative Adversarial Networks (GANs) and
Diffusion models on AWS SageMaker.
● Collaborated with MLops professionals to deploy GAN models on AWS, improving synthetic data quality by 18%
and generating $25,000 in revenue.
• Analyzed 90+ research papers and journals in 2 months to identify gaps in current synthetic data generation
methods.
• Improved data quality using Diffusion models with binary matrix conversion, ensuring 99.89% clean data.
• Implemented metrics-based model analysis like ROC, F1 scores to evaluate performance and ensure
robustness.
• Collaborated with Data Scientists and Software Engineers bi-weekly to provide updates and align on milestones.
Identified a 15% decline in sell-through rates, impacting profitability and regional sales performance.
● Applied Stochastic Gradient Descent (SGD) to improve forecast accuracy by 22%, enhancing sales strategies.
● Delivered progress reports at the Center of Excellence (COE) monthly, facilitating informed decision-making.
● Designed and deployed CI/CD pipelines for automated machine learning model updates, integrating Jenkins and GitLab CI
• Identified inefficiencies in visualization and tracking processes, addressing a 40% gap in data analysis workflows.
• Deployed 3+ ELK Stack Dashboards for real-time visualization, improving metrics tracking and analysis
efficiency.
• Collaborated in daily scrums with engineers and project managers to streamline operations and clarify objectives
Master's in Data Science
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