About Sandesh Gaikwad:
I am a data scientist who loves to explore, analyze, and transform data into meaningful insights. I have a strong academic background in technology and engineering from IISc Bangalore and Savitribai Phule Pune University.
I have worked as a data analyst at CogniTensor, where I developed and implemented various data solutions for clients in different domains. I have experience in building ETL pipelines, data cleaning, recommender systems, inventory management, and data visualization. I have also worked on a novel nonlinear motion observer for stereo vision systems at IISc Bangalore.
I am skilled in machine learning techniques such as supervised and unsupervised learning, transfer learning, and deep learning. I am proficient in Python, SQL, AWS, Azure, and Power BI. I am always eager to learn new skills and tools to enhance my data science capabilities.
I am looking for opportunities to apply my skills and knowledge to real-world challenges and make a positive impact with data. I am passionate about finding innovative solutions that can improve lives and businesses.
Experience
• Developed an end-to-end ETL pipeline using Python, pandas, and SQLAlchemy to extract, transform, and load data from multiple sources into an AWS RDS PostgreSQL database. This work involved optimizing data integration processes, creating scalable data models and schemas, resulting in improved data quality and accessibility. • Designed and implemented an automated data cleaning pipeline to identify and correct errors in datasets, ensuring data quality and consistency. The work included the normalization of data and compliance with ACID principles to ensure data integrity. • Built a recommender engine using collaborative filtering algorithms and purchase history data to enable upselling and cross-selling of protective and safety equipment for one of India’s largest manufacturer. • Designed and implemented a comprehensive inventory management system with interactive dashboards that focused on sales forecast for an intercontinental electric equipment retailer. The system used a combination of client input, weights, and SARIMA models to forecast demand for products and components, and optimize inventory levels. • Developed several dashboards using Python and PostgreSQL that leveraged companies’ proprietary software to provide key insights into data.
Education
I have a Master's degree from IISc Bangalore. My thesis involved writing a numerical solver for PDE equations.
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