Highly motivated, self-starter data-driven analyst and an encouraging manager with a passion for solving complex problems and proven ability to manage multiple products and projects. Exceptional organizational, project management and leadership skills to collaborate with cross functional teams. Equipped with Agile and scrum skills to optimize and improve the business health and product success with expertise in building solutions for changing industry landscapes.
Cryptocurrency Analysis | LaviJ/Cryptocurrency-Analysis: Cryptocurrency Analysis (github.com)
· Data analysis on large data sets of cryptocurrency data to understand what attributes make an impact on the price of the cryptocurrency.
· Achieved 79% accuracy for the price prediction of major coins like Bitcoin using the Bi-directional Long Short-term Memory(LSTM). Used Prophet(R) for trend analysis and NLP based sentiment scores computed on crypto news using text blob.
· ETL and quantitative analysis in Python using Pandas, NumPy and Plotly, Machine Learning modeling using tensor flow, data storage using MongoDB Atlas and data visualization in Tableau dashboards along with webpage creation.
Credit_Risk_Analysis | https://github.com/LaviJ/Credit_Risk_Analysis
· Creation of different machine learning models for classification of credit card holders into high risk or low risk category based on various input data about their financial and credit profile.
· Applied SMOTE for sampling and trained ensemble adaboost model and balanced random forest model. Used A/B testing to select the best performing model.
· Python, Pandas, Jupyter Notebook, sklearn and imblearn used for the above analysis.
Love for fitness, especially yoga and swimming helps me stay fit in order to handle work pressure and achieve work life balance.
Being a lifelong learner keeps me updated about latest technologies, trends and helps me enhance my skills.
Painting is like meditation for me where I see my colorful art pieces come to life.
Cryptocurrency Analysis | LaviJ/Cryptocurrency-Analysis: Cryptocurrency Analysis (github.com)
· Data analysis on large data sets of cryptocurrency data to understand what attributes make an impact on the price of the cryptocurrency.
· Achieved 79% accuracy for the price prediction of major coins like Bitcoin using the Bi-directional Long Short-term Memory(LSTM). Used Prophet(R) for trend analysis and NLP based sentiment scores computed on crypto news using text blob.
· ETL and quantitative analysis in Python using Pandas, NumPy and Plotly, Machine Learning modeling using tensor flow, data storage using MongoDB Atlas and data visualization in Tableau dashboards along with webpage creation.
Credit_Risk_Analysis | https://github.com/LaviJ/Credit_Risk_Analysis
· Creation of different machine learning models for classification of credit card holders into high risk or low risk category based on various input data about their financial and credit profile.
· Applied SMOTE for sampling and trained ensemble adaboost model and balanced random forest model. Used A/B testing to select the best performing model.
· Python, Pandas, Jupyter Notebook, sklearn and imblearn used for the above analysis.
Love for fitness, especially yoga and swimming helps me stay fit in order to handle work pressure and achieve work life balance.
Being a lifelong learner keeps me updated about latest technologies, trends and helps me enhance my skills.
Painting is like meditation for me where I see my colorful art pieces come to life.