Data Scientist candidate in Buffalo, New York, United States

Summary

I am a data scientist with experience in predictive analytics, data exploration, and data visualization. My educational background includes a Masters in professional studies, Data Science from the University at Buffalo, The State University of New York, where I earned a GPA of 3.92/4.0. Additionally, I hold a Bachelor of Technology in Electronics and Communication Engineering from PES University, India.

Throughout my education, I have taken courses in foundational computational science, statistical data mining, cyber security, programming for data science, machine learning, statistics, and database management. I am proficient in programming languages such as Python, R, and C++, and have experience using developer tools and frameworks such as Keras, Scikit-learn, MySQL, Pandas, NumPy, Hadoop, AWS, Apache, Tableau, and Big Query (Google). I have also worked with NLP, MATLAB, Anaconda, CLAN, PRAAT, and Excel.

In terms of work experience, I have worked as a research assistant at the University at Buffalo, where I developed tools to transcribe and annotate spoken language to interface with open-source tool Clan using speech recognition software. I used these insights with the help of NLP and AI/ML technologies to boost and optimize our understanding of factors leading and affecting a childs development with the aid of speech. I also worked as an intern at Agimus Technologies Pvt Ltd. in India, where I spearheaded a team of 5 for product development and projects based on cloud and data-centric applications designed to resolve traffic management issues using vehicular congestion data. I have also served as an intern at AIESEC in India, where I led a team to develop a customer retention model based on the Mackenzie RAD Model with a critical focus on retention and development implemented with the help of a feedback loop methodology and predictive analysis on trends resulting in a 20% increase in retention in the first quarter.

I have earned several certifications, including a Machine Learning certification from Stanford University, a Data Science Professional Certification and Applied Data Science Specialization from IBM, a Machine Learning for Trading certification from the New York Institute of Finance and Google Cloud, and a Digital Transformation Using AI/ML with Google Cloud specialization from Google Cloud. Additionally, I have completed several capstone projects, including Trading Strategies Using Machine Learning, Handwriting & Digits Recognition, Covid Healthcare Trends, and Buffalo Crime Prediction.

Some of my major achievements include building a time series forecasting model to predict stock prices with an accuracy of 83%, deploying integrated LSTM and ARIMA with NLP to perform sentiment analysis on historical data obtained from Yahoo Finance and Kaggle. I have also applied Convolution Neural Networks on multiclass MNIST data to analyze numerical patterns and recognize digits with an accuracy of 96%. Furthermore, I have leveraged Google Big Query to analyze trends and predictions on the various effects of Covid on the GDP and life.

Overall, my background, experience, and achievements make me a highly qualified and capable data scientist. I possess strong technical skills and am adept at communicating technical results to both technical and non-technical audiences.

Expectations

As a data scientist with a strong background in Python and data analysis, I am excited about the opportunity to bring my skills and experience to a new role at your company. I am confident that I can contribute to the team with my proficiency in predictive analytics, data exploration, and data visualization, as well as my practical knowledge in NLP concepts.

In my previous experiences, I have had the opportunity to work on various projects that have allowed me to hone my skills and learn from my peers. For example, my capstone project involved building a time series forecasting model to predict stock prices with an accuracy of 83%. I also led a team to develop a customer retention model, which resulted in a 20% increase in retention in the first quarter. These experiences have taught me the value of collaboration and continuous learning.

In my new role, I am eager to continue to grow and develop as a data scientist, while also contributing to the success of the team and the company as a whole. I look forward to working with and learning from my new colleagues, and am excited about the potential for us to achieve great things together.