Manpreet Kaur Wadhwa

With a passion for data-driven decision-making, keen curiosity to get into world of analytics and a continuous learning mindset, I am excited to bring my skills and experience to this Data Analyst role. Believe in strong work ethic and a sense of responsibility, taking ownership of tasks and working proactively to achieve successful outcomes. I am committed to work collaboratively with cross-functional teams to identify key metrics and develop logical strategies
with enthusiasm for improving business performance. Having experience in teaching Math has enhanced my analytical and structural problem-solving skills. Confidently possess the ability to optimize and communicate complex findings in a clear and concise manner to a target audience(technical/non-technical).

Predicted pricing for Insurance Premium using (Python)

• Performed thorough data exploration to gain insights and understand the underlying patterns, trends, and relationships within the dataset.
• Employed feature selection and extraction techniques to identify the most relevant and informative features within the dataset affecting premium price, improving the model's performance and reducing dimensionality.
• Built a predictive Linear Regression model with an approximate accuracy of 80%

Data and Text Analysis on UK Census Data with Python/Knime

• Performed data cleaning and preparation to generate visualizations using matplotlib.
• Conducted classification analysis on the "Approximated Social Grade" attribute utilizing Decision Tree, Random Forest, and K-nearest Neighbor algorithms.
• Additionally, conducted regression analysis on the count of working hours using Regression Tree, Linear Regression, and Gradient Boosting techniques.

Database creation using PostgreSQL & MongoDB

• Designed and established a clothing store database, including data population and management.
• Executed numerous SQL queries to address diverse business needs and objectives.

Analyzing Data Warehouse of a MOBA gaming business.

• Leveraged Azure to perform comprehensive analysis on a multidimensional data warehouse, utilizing various OLAP operations to extract valuable business insights.
• Conducted evaluation to identify and address ELT/ETL anomalies within the data.
• Collaborated within a cohesive team of four members to craft a compelling and impactful data-driven story and dashboard using Tableau. Effectively communicated key insights and findings through engaging presentations, ensuring the delivery of valuable information.

Brain Tumor Detection and multi-class classification using various CNN models on Jupyter Notebook

• Gathered a comprehensive dataset of brain scans, including MRI and CT images, ensuring the dataset includes samples of both tumor and non-tumor cases.
• Trained a CNN model, fine-tuning the model parameters and hyperparameters to optimize performance.
• Assessed the trained model's performance using appropriate evaluation metrics such as accuracy, precision, recall, and F1-score.
• Validating the model's performance achieving an average accuracy of 75%.
• Sentiment Analysis on Twitter dataset using RNN (Recurrent Neural Network) on Google Colab.