Data Scientist with 1.5 years of experience executing data-driven solutions by generating key business insights that can make a significant impact on the organization. Experience with various projects involving NLP, AIOps, Predictive Modelling, Healthcare Analytics, MLOps am committed to continuous learning and development, staying updated with the latest trends. I am excited about utilizing my skills and experience to make a meaningful impact as a Data Scientist.

Projects:

NYC Taxi Trip Time Prediction-

1. Build a Regression Model using GBM, Decision tree regressor and XG Boost models to predict taxi trip time in NYC for a time of two months.
2. Employed processing techniques such as feature scaling, outlier treatment, missing value imputation and perform temporal sampling to generate train and test data.
3. Applied Lasso and Ridge regulation and used Grid search CV for hyperparameter tuning, which resulted in an adjusted R- squared score of 71% on the test dataset.

Credit Card Default Prediction –

1. Developed a binary classification model using algorithms such as Logistic Regression, SVC, and XG Boost to predict whether a customer will default on credit card payment. Performed missing value imputation using KNN – Imputer, implemented SMOTW boosting to oversample the minority class observation and carried out hyperparameter tuning using Bayesian optimization.
2. Achieved and estimated a reduction in default rate from 8.3% to6.5% and overall performance of the model improved and helps to solve the problem caused by the credit card default.

Skillsets:

ETL Process –

1. Identify the data sources to determine where the relevant data stored, then retrieve the required data from source.
2. Cleanse the extracted data to remove duplicates, handle missing values and inconsistent values. Done mapping of the data elements (help to standardizing the data).
3. Design the target model and load the transformed data into target model.

Data Visualisation –

1. Design the visualization created in PowerBI include dashboards, charts, and reports.
2. Mention the KPIs and metrices which help to track performance. Describe drilldown capabilities for more insights.
3. Technical Skills here are- DAX, Power Query, Data Modelling

Education:

• Master In Statistics, Amity University
• Bsc Statistics, Bsa College (Agra University)

Technical Skills

Certificate

• Azure Data Scientist Associate: Machine Learning Services from SkillSoft.