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Click here or scroll down to respond to this candidateCandidate's Name
Boston, MA PHONE NUMBER AVAILABLE EMAIL AVAILABLEWork ExperienceData Analyst Varsist technologies May 2020 - August 2022 Extracted and processed over 10 million rows of raw sales data from the e-commerce platform's database using Snowflake, ensuring data integrity by identifying and addressing inconsistencies and missing values. Employed Alteryx to rectify over 1,000 data discrepancies, enhancing data quality and reliability. Utilized Snowflake's performance monitoring tools and query history to achieve a 20% improvement in query performance. Conducted statistical analysis on a dataset comprising 2 years of sales data, including calculating summary statistics, identifying trends, and detecting outliers. Identified and defined key performance indicators (KPIs) for sales, revenue, customer acquisition, and retention rates, leading to a 15% increase in data-driven decision-making accuracy. Created over 50 detailed reports and interactive dashboards in Power BI to visually analyze sales trends over time. Integrated Alteryx workflows for efficient data preparation, ensuring data accuracy and streamlining the data pipeline, resulting in a 30% reduction in data processing time for real-time business decisions. Implemented row-level security in Snowflake to establish control over data access for 500+ users, Enhanced data security and privacy measures using Alteryx to monitor and control access, reducing data breach incidents by 40%. Leveraged Python and its libraries to further explore sales data, gaining insights into customer behavior and sales patterns. Conducted advanced analytical techniques to uncover trends, resulting in actionable recommendations that led to a 10% increase in sales. Coordinated with 7 cross-functional teams to ensure alignment on data definitions, metrics, and reporting standards, facilitating a cohesive and unified approach to data analysis and reporting, which improved overall reporting accuracy by 25%. Data Analyst Intern Ducumber May 2019 - December 2019 Developed an advanced deep learning model using Python, OpenCV, and NumPy to address COVID-19 safety measures. The model accurately computes inter-personal distances, issues real-time social distancing alerts, and detects masks. Utilized COCO Dataset for meticulous social distancing analysis, integrating 80 pre-defined objects. Curated a dataset of 2000 images specifically tailored for mask detection, enhancing the model's robustness and efficiency in real-world scenarios. Implemented a Mobile-Net-v2 architecture-based model for mask detection, allowing for efficient computation and deployment. The model successfully identified violations and ensures adherence to mask-wearing protocols. Evaluated the accuracy of the mask detection system, achieving an accuracy rate of 93.92% in distinguishing between masked and unmasked individuals. This high level of accuracy is critical for effectively implementing and enforcing public health guidelines. Monitored and refined the model's performance based on user feedback and real-world data, implementing improvements and updates to maintain high accuracy and reliability. ProjectsMulti-class classification with dry bean dataset [python] September 2023 - December 2023 Utilized NumPy and Pandas libraries to clean the dataset to remove highly correlated features and drop outliers and draw insights. Created custom written Logistic Regression class which takes tolerance and learning rate as inputs utilizing a one vs rest sigmoid cost function that implements newton-CG gradient descent optimization, achieving an accuracy of 87% on the test dataset. Implemented a Nave Bayes model with efficient computation of prior and posterior probabilities using SciPy, yielding a 65% accuracy, while the built-in Gaussian Nave Bayes model achieved a faster runtime and higher accuracy at 70%. Therapy through arts analysis [MYSQL] January 2023 - April 2023 Developed ER (Entity-Relationship) and UML (Unified Modeling Language) diagrams to meticulously craft a logical model, providing a visual representation of data structures and relationships. Executed the implementation of 12 tables, views, and indexes, strategically optimizing data storage and retrieval processes, contributing to a 30% improvement in query performance and system efficiency. Applied 3NF normalization techniques to the database, ensuring data consistency and eliminating redundancy to enhance overall data integrity, reducing data anomalies by 40% and ensuring the highest level of data accuracy. Skills Languages: Python, C, C++, R Database Technologies: MS SQL Server, MYSQL, MongoDB Cloud Technologies: AWS (Athena, Redshift, S3, RDS, Lambda), Snowflake Tools /Frameworks: Tableau, Power BI, Microsoft Excel, Alteryx, Looker, NumPy, Pandas, TensorFlow, Matplotlib, Matplotlib, Seaborn, Keras, Pytorch Algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forest, Support Vector Machines, Nave Bayes, K-means and KNN clustering, Principal Component Analysis, T-SNE, Hierarchical Clustering Certifications Google Data Analytics Certificate AWS Academy Cloud Architect Astronomer Certification for Apache Airflow Fundamentals EducationMaster of Science, Data Analytics and Engineering Northeastern University - Boston, MA Bachelor of Technology, Electronics and Communications Engineering Osmania University - Hyderabad, TS |
