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Click here or scroll down to respond to this candidateCandidate's Name
Chicago, IL 347-874-0653 https://LINKEDIN LINK AVAILABLE EMAIL AVAILABLE GitHub SummaryData professional with 2+ years of experience in data analysis, data science, and business analysis. Proficient in machine learning, cloud platforms (AWS, Azure), and tools like Python, SQL, PowerBI, and Tableau. Skilled in predictive modeling, feature engineering, and delivering actionable insights to optimize business performance.EDUCATIONIllinois Institute of Technology Chicago, ILMaster of Science in Data Science September 2022 May 2024 Top recipients of Graduate Pathway Scholarship Relevant Coursework: Machine Learning, Big Data Technologies, Applied Statistics, Data Preparation and Analysis, Database Organization, Statistical Learning, Probability and Statistics, Monte Carlo Methods. SKILLSProgramming Languages & Databases: Python, MySQL, R, C++, Bash, MATLAB, NoSQL, MongoDB, PostgreSQL, HTML, NodeJS Libraries & Frameworks: NumPy, Pandas, Matplotlib, TensorFlow, OpenCV, Spark, Bootstrap, Scikit learn, Streamlit, Pyspark Cloud Platform: AWS S3, AWS Redshift, AWS Sagemaker, Azure SQL, Databricks, Azure Synapse Analytics, GCP, Oracle Tools: Power BI, Tableau, MS Excel, Google Sheets, MS Word, MS PowerPoint, Jira, SAP, GitHub WORK EXPERIENCELABELMASTER Chicago, ILData Science Intern January 2024 May 2024 Pioneered a real-time price guidance system using ML modelling and statistical hypothesis techniques, leveraging Azure Data Lake and PySpark in Azure Databricks, resulting in a 15% revenue increase. Designed robust Azure SQL data warehousing for efficient storage of transactional data. Engineered features including price sensitivity, company size, and geographical location, leading to enhanced business insights and improved customer satisfaction. Enhanced pricing strategies using clustering analysis in Python, boosting quote acceptance rates by 10%. Visualized insights with PowerBI, delivered a Streamlit dashboard, and automated tasks with Microsoft Power Apps, improving decision-making efficiency. MOVING WALLS INDIA PRIVATE LIMITED Chennai, IndiaData Analyst November 2021 - August 2022 Leveraged Amazon SageMaker for real-time data processing, achieving 90% accuracy in predicting audience migration patterns. Created Tableau dashboards integrating Redshift data for comprehensive audience behaviour analysis, increasing marketing effectiveness. Assessed traffic data for 50 campaigns, ensuring accurate insights for campaign planning. Generated weekly & monthly post-campaign reports for 30+ campaigns, optimizing future campaigns. Explored data trends using Redshift's advanced analytics features, performing complex tasks like cohort analysis and trend forecasting to aid predictive model development. Initiated advanced data models for audience segmentation and targeting, resulting in a 20% increase in campaign precision and engagement. Global Shala St Louis University Chennai, IndiaData Analyst Intern September 2021 November 2021 Led a team of 5, achieving a 14% boost in campaign success by analysing raw data with feature engineering and applying statistical modelling and clustering techniques, yielding a 16% cost reduction. Investigated 10 Facebook ad campaigns using diverse metrics and methods like gradient boosting, achieving a 6% cost reduction, and providing actionable marketing insights.Cloud Pencils Private Limited Chennai, IndiaData Analyst Intern May 2020 August 2021 Employed market data and machine learning algorithms to identify high-potential backers for crowdfunding campaigns on the company's Web3 platform. Developed recommendation systems to personalize campaign exposure, leading to a 45% increase in average contribution amount and a 10% boost in overall funding success rate. Designed and implemented data pipelines using NodeJS and MongoDB to automate data collection and processing for real-time campaign performance analysis. Explored user behaviour data from the OnCloudERP system to identify user needs and pain points and translated data insights into actionable recommendations for product development, leading to the creation of features that improved user satisfaction by 80%. PROJECTSBusiness 360 - Brick & mortar and e-commerce Crafted a multi-view Power BI dashboard for six departments, analyzing Excel and MySQL datasets, optimizing storage, projecting a 10% revenue increase, and engineered an ETL system with SSIS, pooling data from 85+ OLTP sources to provide 95% of decision-making information for executives. Speech Emotion Recognition using Machine Learning Algorithm Trained a MLPClassifier model on diverse datasets (Ravdess, Crema-D, Savee, TESS), achieving 92% accuracy in speech emotion recognition. Applied advanced feature extraction techniques like MFCC, Zero Crossing Rate, and Spectral Centroid. E-Commerce Market Analysis and Insights Analyzed a dataset of 16,832 users and 306 products using machine learning, generating insights on customer preferences and pricing trends leading to a 32% increase in sales leads and a 200% increase in online orders ahead of schedule. Data Warehousing on Telecom Churn Rate Data using AWS Redshift Implemented data warehousing solution on telecom churn data with AWS Redshift. Advanced strategies to reduce churn rates and analyzed influencing factors, achieving 84% accuracy in predicting churn using the XGBoost algorithm. |
