Machine Learning Data Scientist

RIAKANTHA SHIVA KRISHNA

+1-603-***-**** Manchester, NH

************.*****@*****.*** LinkedIn Portfolio Github OBJECTIVE

Obtain a Junior Data Scientist position where I can apply my strong analytical skills, programming expertise, and machine learning knowledge to develop data-driven solutions and support business decision-making. EDUCATION

Master’s Degree, New England College 2023 - 2025

Data Science, (Grade: 4.0)

Bachelor of Technology, K.G. Reddy College affiliated to JNTUH 2018 - 2022 Electronics and Communication Engineering.

Intermediate, Narayana Junior College affiliated to TSBIE 2016 - 2018 MPC.

10th Grade, Kendriya Vidyalaya No.1 Golconda affiliated to CBSE 2015 - 2016 SKILLS

Programming Languages Python, R, C/C++, HTML

Database MySQL, sqlite3

Data Visualization Tools Matplotlib, Seaborn, Tableau, Power BI Machine learning libraries scikit-learn, Keras, TensorFlow Other Skills Data Preprocessing, Feature Engineering, Web Scraping (Beautiful Soup and Selenium), Data Structures CERTIFICATIONS

Coding Ninjas Introduction to Python - Training Certificate (Certification Link) Aug 2020 - Oct 2020 PROJECTS

Sales Analytics Project (Role Simulation: Junior Data Analyst at Atliq Hardwares) SQL, Power BI

• Solved 10 real-world business requests from top management using advanced SQL and Power BI, simulating the responsibilities of a junior analyst.

• Delivered key insights like a 16.67% growth in unique products (2021 vs 2020), top-performing segments, and Retailer’s 72% share in gross sales.

• Created interactive dashboards a stakeholder-ready presentation to visualize KPIs such as monthly sales trends, top discounts, and product rankings. (GitHub Repository Link) Marketing Campaign Optimization

Python, Machine learning

• Conducted exploratory data analysis on a dataset with 2240 data points and 29 features to enhance marketing strategies.using visualization tools like Matplotlib, Seaborn, and Tableau.

• Implemented K-Means clustering and determined the optimal K value using silhouette score and elbow method.

• Developed a predictive model using a soft voting classification algorithm to forecast customer responses. (GitHub Repository Link)

Intel Image Classification

• Designed a convolutional neural network (CNN) for image classification using data augmentation techniques.

• Trained on a dataset of 14,034 images categorized into six labels (buildings, forest, glacier, mountain, sea, street).(GitHub Repository Link)

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