My journey in the data realm has equipped me with a diverse skill set, including data science, Python and C++ development, SQL proficiency, and data visualization.
As a dedicated and enthusiastic professional, I am truly passionate about the vast array of opportunities within this
field. Throughout my journey, I have cultivated a versatile skill set that extends beyond traditional data science. My
expertise encompasses data analysis, statistics, and machine learning, along with Python development. Python empowers me
to create sophisticated software solutions that seamlessly combine creativity with problem-solving. My proficiency in
C++ further bolsters my programming capabilities. I excel in SQL, skillfully managing and manipulating data to derive
analytical insights. Data visualization is another strength of mine, using tools like Tableau to transform intricate
data into actionable insights. The ever-evolving nature of data science continues to ignite my enthusiasm for continual
learning and personal growth in this dynamic field.
I am proficient in the following cutting-edge technologies with which I have been actively involved recently.
Application analyst
Mar 2021 – Aug 2021
New Relic, AppDynamics, iOS, Android
Cyber Security Analyst
Jan 2021 – Mar 2021
Python, Nessus, OpenVAS, Wireshark, Nmap, Metasploit, Burp Suite
Utilized data-driven visualizations using Pandas, Matplotlib, Seaborn, and Numpy libraries, resulting in and increase in user engagement and a reduction in bounce rate. Engineered a diverse range of machine learning models, from SVM to deep learning architectures like CNNs and RNNs, delivering outstanding performance in NLP tasks, boosting accuracy by 20% and reducing false positives by 15%. Employed metrics such as accuracy, precision, recall, F1-score, and ROC AUC to comprehensively evaluate model performance, resulting in a 15% increase in overall prediction accuracy and improved model reliability.
Achieved a 97% accuracy on a binary classification problem by leveraging a dataset of 3000 MRI brain images; Applied inception V3 model to revolutionize medical diagnosis and improve patient outcomes. Programmed a variety of machine learning algorithms, including SVM, Logistic Regression,kNN and Naive Bayes and Deep learning Architecturtes, VGG-16,VGG-19, and Inception V3 in Python. Implemented image processing techniques, including Connected Component Analysis, HOG, SIFT, ORB, PCA, and thresholding, to preprocess and extract relevant features from MRI images, enhancing diagnostic accuracy by 25%.
The Netflix data visualization project showcased compelling visualizations of streaming data. It provided valuable insights into user behavior, content preferences, and viewership patterns. Through interactive graphs and charts, it revealed trends, such as peak viewing hours and popular genres, enabling data-driven content recommendations and strategic decisions. This enhanced user engagement and content personalization on the platform, ultimately improving the overall streaming experience for Netflix subscribers.
The bot's primary objective is to efficiently identify customer intents and automate related conversations. Initially focusing on specific tasks such as nurturing leads with personalized emails, intelligently handling abandoned chats, rescheduling missed meetings, verifying chat leads, and sending meeting reminders ensures early customer success and fosters tool adoption.
The Ecommerce Customer Churn Analysis and Prediction project successfully implemented machine learning models and data analysis techniques to identify factors influencing customer churn. It utilized features like customer behavior, demographics, and purchase history to predict churn with high accuracy. The project's outcome aids in proactive customer retention strategies, improving business sustainability.
Weather forecast prediction employs meteorological models and historical data analysis to estimate future atmospheric conditions. It involves numerical simulations of various factors, including temperature, pressure, humidity, wind patterns, and precipitation. Advanced algorithms assimilate real-time data from satellites, radar, and ground-based sensors to continually refine predictions, providing forecasts with varying accuracy for specific time frames and geographic regions.
I have actively engaged in competitive programming on platforms like LeetCode, GeeksforGeeks, and HackerRank, where I have successfully solved numerous Profiles challenges and problems. You can verify my solved problems and view my badges on these platforms to assess my proficiency and achievements. Additionally, I have contributed to StackOverflow.