Data Science Analyst

AKH;p.ILA KORRAPATI

**.******@*****.*** +1-404-***-****

EDUCATION

UNIVERSITY OF NORTH TEXAS Sep 2022 – Dec 2023

Masters of Science in Data Science, CGPA: 3.6l,.

GITAM UNIVERSITY Jun 2018 – May 2022

Bachelors of Technology in Computer Science and Engineering, CGPA: 3.55

TECHNICAL SKILLS

WORK EXPERIENCE – (2+ YEARS)

Data Science Intern - MyEdMaster LLC Jan 2024 – Aug2024

Executed a pioneering neuromarketing study analyzing EEG signals during product ads to predict purchasing behavior .

Developed a cascade model integrating SVM, Decision Tree, Gradient Boost Classifier, RBF Neural Network, and Deep Neural Decision Forests, comparing outcomes for insights. Provided actionable insights for advertising strategies, collaborating across teams and staying at the forefront of neuro-marketing trends.

Research Assistant-UNT

Developed an ML model for disease prediction using K-Means clustering to segment patient data and explore risk factors, trained LSTM model on annotated data to identify potential diseases within the AWS SageMaker pipeline •optimized model training using mini-batch gradient descent, reducing training time by 20%, and conducted client surveys to gather additional data, leading to a 25% improvement in data-driven decision-making • Built an educational website with HTML, CSS, and JavaScript, integrated an interactive chatbot to address student queries related to subject-specific resources such as videos and written study materials in a personalized manner • Utilized multi-model LLMs (Mistral 7B and Llama2-34B) driven by LangChain and Python agents to analyze user behavior, classifying users into 4 groups and providing tailored explanations and real-world examples.

Data Analyst Intern-Inn Data Analytics Aug 2021 – July 2022

Analyzed customer behavior data, leading to a 20% increase in engagement by refining marketing strategies.

Built dashboards with SQL and Power BI to track purchase trends and KPIs .

Conducted segmentation analysis for targeted campaigns, improving ROI by 15% .

Automated reporting workflows, reducing manual effort by 30%.

Presented key insights to stakeholders and provided actionable recommendations, resulting in a 15% increase in customer retention and 10% growth in sales.

Utilized RFM (Recency, Frequency, Monetary) analysis to identify high-value customers and develop targeted marketing campaigns.

Python Programming Intern-GITAM University Jan 2021 - Aug 2021

●Automated student marks aggregation system using Python, integrating web scraping (Selenium, Beautiful Soup) and data processing (Pandas).

●Developed data visualizations in Seaborn, analyzing grade distributions, question difficulty, and performance trends.

●Leveraged insights to identify improvement opportunities in student exam preparation and question setting.

●Skilled in creating scalable web applications with Django and Flask, using Git for version control and front-end technologies for responsive designs.

Other Projects

Developed an LLM-driven chatbot Chrome extension with Gradio UI, enhancing student interaction with educational platforms like YouTube, GitHub, class recordings, and the web.

●Utilized various machine learning models such as logistic regression, decision trees, random forests, and support vector machines.

●Contributed to industry practices by implementing automated credit card approval methods like those used by financial institutions.

●The outcome highlights the effectiveness of employing advanced modeling techniques in forecasting Black Friday sales trends, enabling more informed decision-making in discounting strategies and promotional planning.

Designed an API for cricket, a prominent sport, utilizing Data wrangling and manipulation techniques using Python

Certifications: Machine Learning, Python, Data Visualization, Database Management

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