Data Analyst Analysis

Boston, MA *(***)-***-ARYAK **** bodkhe.UMESH *@************.****** edu Linkedin Github

EDUCATION

Master of Science in Data Analytics Engineering Northeastern University, Boston MA Sep 2022 - May 2024 Master of Business Administration, Bachelor of Technology Narsee Monjee Institute of Management Studies, India Jul 2017 - May 2022 TECHNICAL SKILLS

Programming Python (seaborn, matplotlib, NumPy, pandas), MySQL, NoSQL, R, R shiny, HTML, CSS Visualization tools Tableau, Microsoft Power BI, Data Wrapper, Flourish, Microsoft Excel, Google Sheets, Google Analytics IDE & Tools GitHub, Microsoft Outlook, Jupyter Notebook, R-Studio, AWS, Streamlit, Talend, Snowflake, Figma Core Skills Data Analysis, Data Visualization, Databases, A/B Testing, Machine Learning, Neural Networks PROFESSIONAL EXPERIENCE

Data Analyst Intern Ceinsys Tech LTD, India May 2021 - Sep 2021 Technology stack: Excel, Tableau, SQL

• Optimized sales transaction mapping by employing Excel functions like VLOOKUP, resulting 20% increase in efficient data management

• Delved into sales transactions of over 50 BD personnel across 5 regions using Tableau, unearthing performance insights that catalyzed a 15% increase in new market penetration

• Collaborated with a data team on a project focused on customer churn prediction, leading to a 30% reduction in customer churn rate and providing insights for potential revenue loss mitigation Teaching Assistant Northeastern University, Boston MA Sep 2023 – Dec 2023

• Evaluated assessments and led interactive lab sessions, offering targeted feedback to enhance academic performance

• Hosted regular office hours to provide personalized academic support, ensuring students grasp key digital manufacturing concepts ACADEMIC PROJECTS

Stock Price Prediction Jan 2024 - May 2024

Technology stack: Python, SQL, Deep Learning Models

• Engineered a Deep Learning model with Bi-LSTM architecture and time series analysis for accurate predictions of future stock values

• Utilized Apple Inc.'s historical stock data from 2015 to 2018 to accurately predict stock prices for the year 2019

• Attained an 86.8% accuracy by comparing predicted stocks with real-time data, providing valuable insights for investment decisions Brazil O-list E-commerce Data Analysis using AWS Sep 2023 - Dec 2023 Technology stack: AWS services – SQL, Glue, Lambda, Athena, S3, Quicksight

• Pioneered the development of an AWS cloud data pipeline tailored for Brazilian e-commerce data, utilizing Lambda functions and AWS services, reducing data processing time by 20%

• Achieved a 15% improvement in data integrity and reliability by optimizing storage and ETL processes with S3 and Glue, resulting in a 25% reduction in data errors

• Enabled interactive analysis and visualization of processed data via Athena and QuickSight dashboards, leading to a 30% increase in actionable insights derived from the data

Strategic Data-Co Global Supply Chain Analysis Mar 2023 - Apr 2023 Technology stack: Microsoft Excel, SQL, Tableau, Google sheets

• Developed a Tableau dashboard to optimize Data-Co Global's supply chain, with KPIs including on-time delivery rate (95%), the average time to ship (3 days), and CLTV ($2,500)

• Analyzed sales performance by department, market, region, and customer segment, identifying top-selling products

• Utilized a combination of structured and unstructured data to generate insights, including identifying late delivery risks in the Southeast region (8% of total orders) and total shipped items increasing by 15% from 2017 to 2018 Credit Card Approval Prediction Jan 2023 - Apr 2023 Technology stack: Python, Pandas, NumPy, scikit-learn, XG Boost, SVM, Logistic Regression, Random Forest, Decision Tree

• Conducted Exploratory Data Analysis (EDA) to unveil correlations for predicting credit card approval outcomes, achieving a correlation coefficient of 0.85

• Implemented preprocessing techniques including outlier removal and SMOTE for dataset balancing, resulting in a balanced dataset with a 1:1 ratio between approved and denied credit card applications

• Developed and optimized an XG Boost classification model, achieving significant performance improvements with accuracy increasing from 75% to 83%, and outperforming other classification models Credit Card Approval Prediction Sep 2022 - Dec 2022 Technology stack :MySQL, Python, NumPy, Seaborn, MatPlotlib, Plotly

• Executed thorough data cleaning across 20 tables, mitigating inconsistencies by 98%, and drafted EER/UML relationship diagrams

• Implemented Employed MongoDB and SQL queries, integrating CTEs, enhancing query execution time by 40% to offer cost-effective health insurance

RESEARCH PUBLICATIONs

Optical Mark Recognition with Facial Recognition System, Springer AISC, ICSCSP 2021 Feb 2021 – Feb 2022

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