Nikhil Bhosale

Chicago, IL • +1-773-***-**** • adw40l@r.postjobfree.com • https://www.linkedin.com/in/nikhil-bhosale7 • Github SKILLS:

Programing Languages: Python, R, C++, Oracle SQL, HTML/CSS

Data Science & AI: Machine Learning, Deep Learning, NLP, Computer Vision, Hypothesis Testing, A/B Testing, Statistical Modelling, Regression, Classification, Clustering.

Analytical Tools: Tableau, Power BI, SAP (Material Master), AWS, Azure, Git, SAS

Other Skills: Microsoft Excel, Microsoft Word, Microsoft PowerPoint, ChatGPT PROFESSIONAL WORK EXPERIENCE

Data Scientist – Intern, Global Shala, Chicago, IL 2022 - 2022

Gathered business requirements from clients to create reports that impact business strategies.

Created dashboards and data insights to analyze and prove hypothesis on identifying 75% ideal market locations and business opportunities.

Extracted data from various data sources in the business and consumer domain, transformed extracted data as per client requests using SQL, Tableau, Microsoft Excel, and Python.

Used fuzzy matching algorithm to accurately fetch 80% of data by locations in consumer domain for competitor analysis.

Communicated data evaluation outcomes and updated requirements to data vendors resulting in accurate analysis.

Developed an efficient automated tableau dashboard to summarize KPIs for various businesses.

Built comparison charts to evaluate percent differences in the annual revenue per brand for the apparel industry. Application Development Associate – Accenture, India 2021 - 2022

Teamed up with American MNC on Vendor, Customer & Master Data Project to migrate acquired company data into SAP

(Atlas & MDG) assessed data quality of master data highlighting irregularities & creating data profiling report improving data quality by 36%.

Gathered client requirements & created 400+ UINs for 28+ countries using SAP & achieved successful go-lives for 15 companies across 3 different companies and helped reduce accounting & costing errors of products by 20%.

Designed & developed a pipeline to detect and localize steel defects on 13000+ images containing 4 types of defects using CNN, Transfer Learning & Resnet to improve the quality of manufacturing & localizing defects found in steel manufacturing.

Extracted data from multiple online sources using API & web scraping for our client Volvo, performed sentiment analysis on those datasets using NLP, assembled an automated pipeline using Python to process multiple datasets, reducing filtration & cleaning time Conceptualized & Implemented a full-fledged web app operating on Microsoft Power apps, devising an automated workflow using Microsoft Power Automate to collect & submit information, reducing manual work for 30+ team members.

Extracted & loaded data from multiple data sources, handled large volumes of data, performed data analysis on the datasets using Oracle SQL and Excel functions like BA, VLOOKUP & Pivot tables.

Utilized Tableau & Excel functions to perform statistical analysis; assessed monthly review findings to the client. PROJECTS

Healthcare Heart stroke analysis, Illinois Institute of Technology, Chicago, USA April 2023 – May 2023

• Used supervised ML algorithms - logistic regression, KNN classification in Python and R to predict heart strokes in patients using t test and chi square test.

• Compared algorithms using ROC curves and accuracy matrix to identify a better classification model to predict strokes.

• Predicted KNN classification as 85% better model than Logistic Regression which had 72% accuracy to predict strokes. Telco Customer Churn Analysis, Illinois Institute of Technology, Chicago, USA Nov 2022 – Jan 2023

• Used quantitative and complex datasets to develop an understanding of customer behavior using Python.

• Implemented EDA, data cleaning, Data exploration using histogram, boxplot, correlation matrix and build a model using Decision Tree Classifier and Random Forest Classifier using one hot encoding method and SMOTEENN.

• Predicted churns using Random Forest Classifier and predicted customer churn which had 94% success rate. NLP - Decease Classification Using Drug Reviews, Illinois Institute of Technology, USA Feb 2023 – April 2023

Developed an NLP project to predict medical conditions of patients by analyzing drug reviews using Naive Bayes Machine Learning model with TF-IDF.

Utilized preprocessing techniques such as tokenization, stop word removal, stemming or lemmatization to optimize data for training and testing.

Project demonstrates ability to apply NLP and ML techniques in healthcare industry to assist doctors and pharmaceutical companies.

Airbnb TABLEAU Visualization, Illinois Institute of Technology, Chicago, USA Nov 2022 – Dec 2022

• Analyzed and researched how various factors like Bed availability, average prices, zip code, top regions affect the Price of the properties and plotted the graphs of target attributes as a dynamic dashboard.

• Generated advanced Tableau dashboards with context/type of property, zip code and Year filters for forecasting and statistical uses. Presented and documented the findings to people of different types of interests. Hardware Implementation of RNN Using FPGA, University of Pune, India Jan 2021 – Jul 2021

• Created functional model of Recurrent Neural Network and checked efficiency and architecture of RNN on PYNQZ2

• Implemented Recurrent Neural Network RNN by using LSTM and got 87% accuracy by using KNN classification model.

• Published Research Paper in the Journal of Huazhong University of Science and Technology on Hardware Implementation of RNN Using FPGA with 2 colleagues and Professor - shorturl.at/fvz56.. EDUCATION

ILLINOIS INSTITUTE OF TECHNOLOGY, CHICAGO, IL May 2024 M.S. in Information Technology & Management (Data Analytics and Management) GPA-3.7/4.0 Relevant Courses: Programming for Data Analytics, Advanced Topics in Data Management, Data Mining, Data Warehousing, Data Security, Machine Learning.