Data Analyst

HARSHITHA GOKANAKONDA

********************@*******.*** 469-***-**** www.linkedin.com/in/harshi99

**** ********* **, **** *******, CO, 80528

EDUCATION

The University of Texas at Arlington, Arlington, Texas AUG 2021 – July 2023

Master of Science in Computer Science

Course Work: Cloud Computing & Big Data, Web Data Management, Data Mining, ML, AI, DBMS

International Institute of Information Technology Bhubaneswar, Odisha, India AUG 2017 – June 2021

Bachelor’s in computer engineering

Course Work: Design & Analysis of Algorithm, Computer Networks, Data Structures, Operating Systems

TECHNICAL SKILLS

Programming Languages & IDEs

Python, Java, Java Script, C++, R, SQL, HTML, XML, Visual Studio, PyCharm, R studio, Jupyter

Machine Learning & Predictive Modeling

Scikit – Learn, TensorFlow, Machine learning Model Deployment

Database

MS Access, MySQL, SQL Server, Oracle SQL, Amazon Web Services (AWS), Relational Database Management (RDMS), T-SQL, Monet DB, Teradata, PostgreSQL

Statistical Analysis

Exploratory Data Analysis (EDA), A/B Testing, Time-Series Analysis

Visualization Tools

Tableau (Desktop, Server, Prep Builder & Reader), Power BI (Services), Microsoft Excel, Matplotlib

Data Processing & Management

Spark SQL, Databricks, AWS S3, Snowflake, Redshift, MySQL, SAP

Operating Systems

Microsoft Windows 7,8,10, XP / Vista, Mac OS

Version Control tool

Git, SVN

Methodologies

Waterfall, Agile Scrum, SDLC

Other tools

MS Visio, MS Access, Outlook, SharePoint, Git, ServiceNow, Jira, MS Purview, MS Suite, KP

EXPERIENCE

Signet Jewelers – Remote

Data analyst

Jan 2023 – Present

Administered the collection, analysis, and interpretation of large-scale datasets driving a 20% increase in cross-selling opportunities and $1.2M in additional revenue.

Incorporated Spark SQL, Databricks, Excel and SAP to automate the loading of data from AWS S3 to Snowflake tables, accelerating the process by 70% and enhancing overall data management efficiency.

Designed and maintained Excel spreadsheets for budgeting, forecasting, and financial modeling, providing valuable insights for strategic planning and resource allocation.

Implemented SAP modules across finance, procurement, and inventory management, optimizing enterprise resource planning systems for enhanced operational efficiency.

Formulated advanced SQL queries, utilized for data manipulation, and leveraged SAP for business processes to calculate and analyze sales performance metrics, the outcome was a notable 15% increase in quarterly revenue and a significant 20% improvement in forecasting accuracy.

Analyzed and interpreted vast operations and customer behavior data sets to identify cost-saving opportunities; reduced operational expenses by $500k annually through targeted process optimizations.

Utilized advanced Excel functions and macros to streamline financial analysis, resulting in improved decision-making accuracy and significant reduction in manual effort.

Configured SAP reports and dashboards to visualize key performance indicators, empowering stakeholders to make data-driven decisions and monitor business performance in real-time.

Implemented Tableau dashboards to track Data Lineage and Metadata, giving the business real-time visibility into data sources and dependencies, leading to a 40% reduction in data processing time.

Orchestrated the implementation of Python scripts to facilitate the seamless transfer of metadata from S3 and Snowflake to EDM Reporting mart on Redshift, optimizing Tableau reporting for enhanced data analysis.

Developed and deployed Python modules to extract and load asset data from MySQL source database, ensuring real-time data synchronization with downstream systems; increased data processing speed by 75% and eliminated data discrepancies.

Spearheaded the identification and automation of manual data processes using SQL scripts, Excel formulas, and SAP functionalities, delivering a 30% decrease in data processing time and maximizing team efficiency.

Engineered and executed automated capacity planning reports leveraging Python packages (NumPy, Pandas, Matplotlib); slashed manual report generation time by over 70% and fortified data accuracy for strategic decision-making.

Steered SQL and Python scripts to perform comprehensive data validations, ensuring accuracy and consistency of metrics in Redshift, resulting in a 25% reduction in data discrepancies and fortified data integrity.

Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing data mining, Excel modeling, and reporting solutions that scale across a massive volume of structured and unstructured data, integrating with SAP systems for streamlined operations.

PhonePe, Bangalore, India

Data Analyst

Aug 2020 – JULY 2021

Conducted exploratory data analysis (EDA) on large datasets to extract meaningful insights, contributing to a 15% improvement in transactional efficiency.

Implemented machine learning models to optimize fraud detection algorithms, resulting in a 25% reduction in fraudulent transactions within the first three months.

Collaborated with cross-functional teams to identify key business questions and translated them into data-driven solutions, improving decision-making processes.

Utilized Python and scikit-learn for developing predictive models, such as customer churn prediction and user segmentation, enhancing targeted marketing strategies.

Played a pivotal role in designing and implementing A/B tests, analyzing user behavior patterns, and providing actionable recommendations for product optimization.

Created and maintained automated dashboards using Tableau, providing real-time insights into key performance indicators (KPIs) and facilitating quick decision-making.

Utilized Excel functions, formulas, and pivot tables to extract meaningful insights from large datasets, contributing to a 15% improvement in transactional efficiency.

Applied Excel skills to enhance the accuracy of forecasting models during time-series analysis, resulting in a 15% improvement in forecasting precision.

Actively participated in weekly team meetings, presenting findings and insights derived from data analysis, and providing valuable input for strategic planning.

Collaborated with the engineering team to integrate machine learning models into the existing data infrastructure, ensuring seamless deployment and scalability.

Contributed to the development of a recommendation system using collaborative filtering, enhancing the user experience and increasing engagement by 20%.

Engaged in continuous learning and professional development, staying updated on the latest advancements in machine learning and data analytics through online courses and industry publications.

Proficient in Excel functions, formulas, and pivot tables to extract meaningful insights from large datasets, contributing to a 15% improvement in transactional efficiency.

Applied Excel skills to enhance the accuracy of forecasting models during time-series analysis, resulting in a 15% improvement in forecasting precision.

Developed DAX measures to analyze and visualize key business metrics, contributing to a 20% improvement in the accessibility and interpretation of critical data.

Leveraged DAX functions within Power BI for comprehensive time-series analysis, identifying temporal patterns and trends crucial for refining forecasting models.

Incorporated DAX time-intelligence functions to enhance the accuracy of transaction volume forecasts, resulting in a 15% improvement in forecasting precision.

Dell Technologies, India

Data Analyst

DEC 2019 – JULY 2020

Involved in SDLC Requirements gathering, Analysis, Design, Development, and testing production of the application using the Waterfall model.

Created various types of data visualizations using R(ggplot2), Python (NumPy, Pandas, Matplotlib, SciPy), and Power BI.

Used Python APIs for extracting daily data from multiple vendors.

Used packages like ggplot2 in R Studio for data visualization and generated scatter plots and high-low graphs to identify relations between different variables.

Worked with SQL, Stored Procedures, Triggers, and SQL queries to access necessary data.

Excellent Analytical and communication skills, working in a team and ability to communicate effectively.

Strategic Planning for improving the organization’s efficiency.

Self-starter and able to handle multiple tasks based on priorities.

Designed and developed various Ad hoc reports for different teams in MS Excel.

Strong analytical and problem-solving skills with the ability to plan, prioritize, and work efficiently in a multi-tasking environment.

Involved in Data Migration and Data distribution testing.

Used Power BI to design multiple scorecards and dashboards to display information required by different departments and upper-level management.

MedTourEasy, India

Machine learning Intern

MAY 2019 – AUG 2019

Spearheaded a cutting-edge project to develop a Sign Language Recognition system using deep learning techniques to bridge communication gaps for the hearing-impaired community.

Utilized Python as the primary programming language and TensorFlow framework for building and training the deep learning models.

Preprocessed a diverse dataset of sign language gestures, including cleaning, normalizing, and augmenting the data to improve model generalization.

Designed a Convolutional Neural Network (CNN) architecture to capture spatial features and a Bidirectional Long Short-Term Memory (Bi-LSTM) network to model temporal dependencies in the sign language sequences.

Measured the model's accuracy, precision, recall, and F1 score, achieving an impressive accuracy of over 90% on the test set.

Contributed to the documentation of the project, including detailed explanations of the model architecture, data preprocessing steps, and deployment instructions.

Certifications

Python Nanodegree from Udacity October 2018

Machine Learning for Everyone from COURSERA March 2019

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