Skills

Leadership & Management

• Team Leadership and Development

• Strategic Project Management

• Performance Evaluation and Coaching

• Client Relationship Management

• Cross-Functional Collaboration

• Process Improvement and Optimization

Analytical Skills

• Data Cleaning and Preprocessing

• Feature Engineering

• Model Evaluation and Validation

• Descriptive and Inferential Statistics

• Data Wrangling

Product Analytics

• Product Strategy Development

• A/B Testing and Experimental Design

• Root Cause Analysis

• Metrics Analysis and Reporting

Technical Skills

• Programming Languages: Python, SQL

• Advanced Excel (Formulas, Pivot Tables, Data Visualization)

• Libraries & Frameworks: Pandas, Numpy, Scikit-learn, TensorFlow, PyTorch

• Data Visualization Tools: Power Bi, Tableau, Matplotlib, Seaborn

• Machine Learning Techniques: Supervised Learning (Linear Regression, Decision Trees, Random Forests)

• Unsupervised Learning (Clustering, K-Means)

• Neural Networks (CNN, RNN, LSTM, GANs)

• MLOps: Model Deployment, Monitoring, and Maintenance

• Statistics: Probability Theory, Hypothesis Testing, Regression Analysis

Projects

Hypothesis Testing - Python

• Analyzed the influence of factors like working days, seasons, and weather on electric cycle rentals.

• Selected appropriate tests, established hypotheses, checked assumptions, and determined significance levels.

• Provided insights and recommendations based on the analysis, even when some assumptions were not met, ensuring a thorough assessment of the factors affecting rental numbers.

E-commerce - SQL 

• Conducted extensive data analysis using SQL in BigQuery.

• Imported the dataset and performed exploratory tasks like checking data types, analyzing order timelines, and customer locations.

• Delved deeper into trends, seasonality, and preferred order times, as well as assessed the evolution of e-commerce orders and economic impact.

• Examined payment-related insights to extract valuable insights and offer actionable recommendations.

Trainee Attrition Analysis - MS Excel 

• Gathered historical data on trainee batches to conduct an attrition analysis.

• Analyzed trainee performance, trends, and tenure over the years to determine the viability of continuing trainee hiring.

• Provided valuable insights and recommendations to management based on the analysis findings.

Customer Segmentation Analysis - Python (Scikit-learn)

• Utilized clustering techniques to segment clients based on behavior.

• Delivered insights that informed targeted marketing strategies, enhancing customer engagement and retention.

Neural Network Implementation - Python (TensorFlow, Keras) 

• Developed a predictive model to assess client risk profiles.

• Improved risk management strategies and enhanced client engagement through data-driven insights.

Predictive Modeling - Python (Scikit-learn) 

• Developed a predictive model to assess client risk profiles.

• Improved risk management strategies and enhanced client engagement through data-driven insights.

Data Visualization Dashboard - Power Bi 

• Created an interactive dashboard to analyze retirement plan performance metrics.

• Facilitated data-driven decision-making for stakeholders by presenting key insights visually.

Product Analytics Case Study - Python, Excel 

• Conducted a comprehensive analysis of product metrics, including A/B testing and root cause analysis.

• Optimized product features and enhanced user engagement based on analytical findings.