I am a Data Science enthusiast with a deep understanding of statistical concepts and analytical practices with three years of experience working with various Data Analytics tools and delivering data-driven business solutions. I believe in making learning a part of your journey no matter what height you reach.
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Experience
Business Analyst, New York University IT Operations Technology Services Support. (Jan 2019 – Current)
• Assisted with the software development lifecycle, from gathering client requirements to training users, testing and documenting newly deployed features and systems.
• Shipping sustainable solutions addressing complex organizational needs with Agile.
• Integration and System Testing using test case management tools like JIRA and Confluence.
• Performed SQL Database Analysis and validation testing to check accuracy of the 13 million square feet of space data.
• Developed Tableau reports for clients to see the status of their space availability with their changes requests.
Business Intelligence Analyst, NYC Department of Sanitation, Bureau of Recycling and Sustainability. (May 2019 – Aug 2019)
• Replaced traditional data processing with the ETL pipeline to expedite the process by 95%.
• Modeled on power BI using DAX and Power query for dynamic dashboards with performance metrics and important KPIs.
• Built process flow charts and deliverables timeline analysis to improve the efficiency of the projects.
• Designed schema and built a database for sub-departments with Microsoft Access and SQL Server.
• Created Data governance guidelines to ensure quality data collection and reduce data pre-processing time by 70%.
• Built an Image Classifier to recognize the category of waste from the object images provided with 78% accuracy.
EndNote Software Citation Assistant, New York University Dentistry. (Dec 2018 – Feb 2019)
• Scrapped data from google scholar using python to build and maintain a library for citation on endnote.
• Rectified and formatted research journals and used EndNote to manage citations with international publication standards.
Data Analyst/ Insights Specialist, Alliance Fiber Ltd, Surat, India. (May 2017 – Dec 2017)
• Analyzed sales for monthly Tableau reports. Proposed strategies resulted in 14% yearly growth and 27% drop in inventory.
• Processed live sensor data from processing plant to look for delays between processes, expedite the process by ~22%.
• Conducted Regression Analysis and other forecasting methods to predict the required production rate with 92% accuracy.
I have past experience working in different roles of Data Science like Business Intelligence Analyst and Data Analyst, delivering Data-Driven solutions and building Automating systems to reduce the redundancy in the work processes and make it more efficient.
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Projects
My most time invested, ongoing project is my personal portfolio where I try to put up two posts every week. This is an initiative to grow professionally and personally by keep learning and building a platform where people can learn some amazing Data Science concepts in the quickest, easiest ways possible. https://shreyash1811.github.io/machine-learning/
User Personalized Recommendation System for Amazon by making use of reviews. (Python) (Sep 2019)
• Developed a system with sentimental analysis and text mining on user reviews to extract user personal preferences.
• Created tag words for products using product reviews and personalized tag words for each user from their reviews.
• Matched user with the products that had the perfect tag words match using k mean clustering and KNN models.
Predicted prospective students and proposed strategy using Funnel Analysis and Persona Building. (R) (Sep 2019)
• Data cleaning using statistical imputation methods, and feature engineering principles. Performed Data Anomaly detection to maintain quality of the data. Rectified unbalanced data using sampling methods.
• Performed Funnel analysis and Persona building to improve convergence rate and target fit prospects with 92%.
• Created Machine Learning models to predict student’s yearly performance beforehand with 94% accuracy.
Predicting news popularity of an articles from internet article trends. (Python) (Mar 2019 – Apr 2019)
• Scrapped article data from Mashable.com, and converted into 60 features using LDA, NLP and sentimental analysis.
• Predicted if an article will be popular with 73% accuracy before publishing it using various ML models and techniques.
Stock Market Forecasting (Python: Numpy, Pandas, Matplotlib, Scipy, Seaborn and beautiful soap) (Jan 2019)
• Scrapped data from Yahoo finance for top Tech-Companies.
• Analyzed Value at Risk and portfolio loss using “Monte Carlo method” and “bootstrap” method with 95% confidence interval. Calculated their ROI, MA and daily return correlation, projected future stock price with 1000 simulations.
• Used fbprophet and forecasted s&p 500 with 0.35% error rate.
Descriptive and Predictive Analysis of Business Case Studies. (R: Ggplot2, tidyr, stringr, dplyr) (Aug 2019 – Oct 2019)
• Data preprocessing and breaking down the insights into actionable business strategies with achievable future projections.