About
👋 Hello there! I'm Nitish Kumar Panigrahi, a dedicated Software Engineer with a passion for problem-solving and a strong foundation in Software Engineering. I am excited to leverage my analytical skills and knowledge gained through my educational journey to make a significant impact in the tech industry. 📚 Education: I hold a Bachelor's degree in Software Engineering from Centurion University of Technology and Management, Bhubaneswar, Odisha. During my academic pursuits, I immersed myself in various aspects of software development, honing my skills in Java, C++, and Python programming languages. My commitment to continuous learning led me to explore diverse areas, including digital marketing and blockchain technology, through certifications from Google Digital Garage and Coursera, respectively. 💼 Internship Experience: As part of my professional growth, I had the privilege of interning with Exposys Data Labs in Bhubaneswar, Odisha. This experience has strengthened my expertise in data science, machine learning, and analytical problem-solving. 🚀 Projects: I am truly passionate about working on real-world projects that challenge me to innovate and grow. Some of my notable projects include: "Chronic Disease Classification" (May 2021 - October 2021): Leveraging machine learning techniques to classify chronic diseases and assist in early detection. "Dress Code Detection" (June 2021 - January 2022): Implementing data science techniques to identify dress codes from images. "Bitcoin Price Prediction" (May 2021 - November 2021): Utilizing data science methods to predict Bitcoin prices and analyze market trends. "CIFAR-10 Dataset Classification" (September 2021 - January 2022): Developing image analytics solutions using Python for image classification. "Tic Tac Toe Game" (September 2021 - January 2022): Creating a fun and interactive game using C++ programming language. "Handwritten Digit Recognition System" (September 2020 - January 2022): Implementing machine learning models to recognize handwritten digits. 🛠️ Skills: Programming: Java, C++, Python, HTML5. Data Science: Data analysis, machine learning, and visualization. Image Analytics: Image processing and classification algorithms. 🔗 GitHub: I love collaborating and sharing my code with the developer community. You can find some of my open-source projects and contributions on my GitHub: [https://github.com/nitishku16] Seeking new opportunities as a Software Engineer to apply my analytical skills and knowledge in Java, C++, Python, and data science.
Work experience
Business Development Associate at Brandzzy, Mar 2025 - Present · 1 yr 4 mos, Bhubaneswar, Odisha, India, Excited to start my journey as a Business Development Trainee at Brandzzy! This role offers a great opportunity to enhance my skills in sales, market analysis, and client relationship management while contributing to business growth. Looking forward to learning from an amazing team, building strategic partnerships, and exploring innovative ways to drive success. Open to connecting with professionals in the field to exchange insights! #Brandzzy #BusinessDevelopment #NewOpportunities
Data Science Intern at Centurion University of Technology and Management, Jan 2023 - Aug 2023 · 8 mos, Bhubaneswar, Odisha, India, Worked on machine learning and data analysis projects, applying statistical techniques and predictive modeling. Developed a chronic disease classification model using Random Forest and SVM, achieving 92% accuracy. Built a Bitcoin price prediction model using LSTM neural networks to forecast daily closing prices. Performed exploratory data analysis (EDA) on sales data, identifying key sales drivers and optimizing marketing strategies. Gained hands-on experience in Python, machine learning, deep learning, and data visualization.
Data Science Intern at Exposys Data Labs, Oct 2022 - Nov 2022 · 2 mos, Bhubaneswar, Odisha, India, Conducted exploratory data analysis (EDA) on a sales dataset containing cost, marketing spend, and profit data for 50 companies. Identified key sales drivers and trends to provide actionable insights for optimizing marketing strategies and profit margins. Applied descriptive statistics, correlation analysis, and data visualization to uncover patterns in sales performance. Developed predictive models to forecast revenue trends and enhance decision-making. Gained hands-on experience in Python, Pandas, Matplotlib, and Seaborn for data analysis and visualization.
