About
Highly accomplished and results-driven Data Scientist with 2+ years of experience leveraging advanced machine learning, data analytics, and statistical modeling to drive business growth and optimize operational efficiency. Proven expertise in developing and deploying scalable AI/ML solutions, performing in-depth data analysis, and leading A/B testing initiatives. Adept at optimizing data pipelines, refactoring code, and translating complex data insights into actionable strategies. Seeking to apply strong analytical and technical skills to complex data challenges in a dynamic environment.
Work
→
Summary
Driving auction performance and revenue growth through advanced data science methodologies and machine learning model deployment.
Highlights
Enhanced auction performance by 8% through data-driven dynamic configurations and parameter tuning, leveraging simulation data and auction insights.
Designed and executed A/B tests and simulation-based Root Cause Analyses (RCAs) to validate pricing strategies, supporting regional rollouts and maximizing company revenue.
Refactored legacy code modules to improve readability, modularity, and reliability, incorporating robust error handling and fallback mechanisms.
Optimized system and data pipelines, reducing latency by 30% across pricing and auction workflows through API streamlining and memory optimization.
Developed and deployed a CatBoost classification model for real-time price acceptance prediction, utilizing hybrid feature engineering and real-time data pipelines, deployed via Docker/KServe on Google Kubernetes Engine for scalable production.
→
Summary
Provided data science consulting services, focusing on data visualization, LLM optimization, and machine learning model development.
Highlights
Improved client data accessibility and usability by redesigning data visualization techniques, integrating statistical and informational graphics.
Developed and documented structured code for comprehensive client data analysis.
Optimized LLM performance through iterative prompt engineering and modification to achieve highly optimized results.
Engineered AI applications, including a document reader, using OpenAI GPT 3.5 and vector databases for efficient similarity searches on client data.
Developed an electrical signal image classification model by fine-tuning pre-trained Hugging Face transformers and PyTorch modules.
→
Summary
Contributed to data analysis, pipeline automation, and machine learning model development to enhance operational efficiency.
Highlights
Enhanced work efficiency by 10% through the development and optimization of SQL queries on the Redash Platform.
Automated data extraction from Athena queries to S3 using Python pipelines and Redash.
Improved modeling and hyperparameter tuning processes by 10% through automated test report generation using Tensorboard and MLflow, with results stored in Google Sheets.
Resolved and maintained 3 critical Airflow DAGs, ensuring continuous automation.
Contributed to Neural Network model development, improving team efficiency by 5% through collaborative efforts.
→
Summary
Gained foundational experience in data scraping, inventory management system development, and comprehensive data analysis.
Highlights
Constructed comprehensive datasets by scraping data from 7 ed-tech websites, including GFG and Programiz.
Developed a foundational Inventory Management System.
Performed extensive Exploratory Data Analysis (EDA) and visualization on diverse datasets, including US Car manufacturing, Olympic Data, and Breast Cancer, achieving 100% data comprehension.
Skills
Data Analytics & Visualization
Data Visualization, Tableau, Power BI, Data Analytics, Data Science, Data Wrangling, SQL, Analytical Approach, Advanced G sheet, Excel, SQL Joins, Common Table Expressions (CTEs), Seaborn, Matplotlib, JSON Data Manipulation, AWS SageMaker.
Machine Learning & Deep Learning
Machine Learning, Deep Learning, Neural Networks, TensorFlow, PyTorch, Keras, Fine-tuning Pre-trained Models, OpenCV, TorchVision, Pillow, Version Control, Model Deployment, Vision Transformer (ViT), GPT-4, Diffusion Models, Prompt Engineering, Prompt Design.
Deployment
AWS, Google Cloud, KServe, Kubernetes, Single-server Deployments, AWS Lambda, EC2 Instances, Docker.
Programming & Tools
Python, PySpark, Object-Oriented Programming (OOP), Multi-processing, HuggingFace, JIRA.
Professional Skills
Problem Solving, Adaptability, Fast-paced Work Environment, Technical Communication, Teamwork, Customer Focus, Process Improvement, Actionable Insights, Curious Thinking, Passion.
Documentation
Documentation Review, English, Written Communication, Presentation, Google Slides, PPT.