Lakshmi Shreya Kotteda
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Lakshmi Shreya Kotteda

LAKSHMI SHREYA KOTTEDA
Email : ------------ |Tel : ------------ | ------------/in/shreya-kotteda/
SUMMARY
Graduate student and experienced analytics professional skilled in Data Analysis and Visualization using frontline technologies like Python, SQL, and Tableau. A quick learner, taskmaster, and empathetic team member looking to make a meaningful impact with my contributions to the organization.
EDUCATION
MASTER OF SCIENCE in Information Technology and Analytics, GPA: 3.9/4 Jan’21
Rutgers University, New Jersey
RELEVANT COURSEWORK
Business Forecasting, Data Visualization, Business Data Management, Analytics Business Intelligence, Data Science, Business Data Intelligence, Data Structures, Business Intelligence with Visual Intelligence, Project Management.
BACHELOR OF SCIENCE in Computer Science, GPA: 3.8/4 May’19
Gokaraju Rangaraju Institute of Engineering and Technology, India
TECHNICAL SKILLS
• Programming - Python (Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn), R, SQL, Java, C
• Environments - Jupyter Notebook, Spyder, RStudio
• Business Intelligence Tools - Tableau, Power BI
• Machine Learning - Linear/Logistic Regression, Decision tree, Random Forest, Neural Network, K-Means, Computer Vision, Time-series Forecasting
Classification, Clustering Analysis, Association, Data Mining, Visual Analytics
• Development Methodologies - Agile, Waterfall, Hybrid, SDLC
• Databases - Microsoft SQL Server, MySQL, Oracle SQL 11g
• Certificates - Google Analytics, Tableau Specialist, Python for Data Analytics, SQL for Data Science
PROFESSIONAL EXPERIENCE
Data Analyst Intern – People Tech Group, Seattle, WA Jun’20 - Nov’20
Client : AccuWeather
• Extracted data from varied data sources like web browsers and google analytics using optimized SQL queries
• Performed data cleansing, transformation and exploratory data analysis using python to create a centralized data repository
• Crafted intuitive data visualization dashboards using Tableau to help the organization better understand data trends and patterns, to bolster business development
Data Analyst – ESKTEC, Hyderabad, INDIA Apr’18 - July’19
Client: Novartis
• Developed an efficient sales performance report Contest tracker leveraging commercial health care datasets using SQL, that helped Brand Sales Force team of Novartis with effective appraisal management.
• Conducted data cleansing and transformation of client datasets to generate reports which helped improve the sales team’s performance by 12%
• Visualized the reports using Tableau and monitored the calls and samples activities of the Novartis Sales Team
• Identified and Analyzed business and client requirements. Acted as a liaison between management and technical teams
Analyst Intern – Evanston Food Ventures Global Pvt Ltd, Hyderabad, INDIA Feb’16 - Jun’16
• Created interactive dashboards and reports using Tableau for analyzing purchase orders to determine key business metrics
• These visualizations helped the management make critical business decisions to sustain competitive edge in the Market
ACADEMIC PROJECTS
E-Commerce data Customer Segmentation, Rutgers University [Python, EDA, Data Modeling, Excel, Tableau] Sep’20 - Dec’20
• Analyzed the contents of the e-commerce data curating relevant attributes and ran classification algorithms such as Logistic Regression, K-Nearest Neighbors, Decision tree, and Random Forest using Python. Visualized the dataset using Tableau.
Global Terrorism Data Visualization, Rutgers University [Data Visualization, Tableau, Python, Excel] Feb’20 - May’20
• Performed data extraction, data cleaning, and exploratory data analysis on the global terrorism data to examine the seasonality, reason, and effect of terrorism around the world. Created worksheets, dashboards for storytelling using Tableau.
Analysis on Goodreads, Rutgers University [Python, Clustering, Data Visualization, Data Modeling, ETL, EDA] Sep’19 - Dec’19
• Oversaw the team to perform data cleaning, manipulation, and exploratory data analysis using Python in Jupyter Notebook.
• Built a ranked product-based recommendation system for the Goodreads data set of 15k records using K- means clustering for identifying relationships in the data, and K-nearest neighbors for classifying, with 72% accuracy.
Brent Oil Prices Analysis, Rutgers University [R, R studio, Time Series Forecasting] Oct’19 - Dec’19
• Headed the team to forecast the prices of Brent Crude Oil dataset from Kaggle (May 1987 to September 2019) using models like Arima, Season Naïve, Naïve and concluded that Arima was the best fit for the data set with a Root Mean Square Error of 29%. Visualized the dataset using RStudio.
KEY ACHIEVEMENTS
• Student Head, Master of Information Technology and Analytics Student Association (MITSA), Rutgers University, NJ
• Member, Computer Society of India (CSI), GRIET, India