🎯 Aspiring Data Analyst | Data Science | Data Engineering | Management Graduate

I’m passionate about transforming raw data into valuable insights that drive better business decisions. With a background in Management and hands-on experience in Retail Operations, I now focus on Data Analysis, Data Science, Data Engineering, and Business Intelligence.

• General Skills: Exploratory Data Analysis (EDA), Time Series Analysis, Machine Learning, Cloud ETL, Data Engineering
• Programming Languages: Python, SQL
• Visualization Tools: Tableau, Looker Studio, Kibana
• Libraries / Frameworks: TensorFlow, Scikit-Learn, Streamlit, Pandas, NumPy, Matplotlib, Seaborn, SciPy, Feature-Engine
• Data Engineering & Workflow Tools: Docker, Apache Airflow, PostgreSQL, ElasticSearch, Apache Kafka, Apache Hadoop
• Techniques: NLP, Computer Vision, Time Series Forecasting, Kimball Data Modeling
• Modeling Algorithms: Regression, Random Forest, Decision Trees, Neural Networks, Clustering, Dimensionality Reduction
• Cloud & Platforms:
  • Google Cloud: BigQuery, Cloud Storage, Dataflow
  • Others: Hugging Face, Notion

RepliCoin is an experimental blockchain prototype designed to explore a new hybrid consensus mechanism: Proof of Stake and Replication (PoSaR), a fusion of energy-efficient staking and active contribution through data replication.

Tools/Tech: Python, Pandas, Ymal, Matplotlib, Pytest

Evaluated the effectiveness of a marketing campaign using causal inference, comparing treatment vs. control groups to uncover spending patterns, customer behavior, and campaign impact.
Tools/Tech: Python, Pandas, NumPy, Seaborn, Matplotlib, Scikit-Learn, DoWhy, EconML

Analyzed supermarket sales data to uncover customer behavior, sales trends, and key business insights. Built an interactive dashboard for stakeholders.
Tools/Tech: Python, Pandas, NumPy, Scikit-Learn, TensorFlow, Keras, Streamlit

Developed a machine learning model utilizing Artificial Neural Networks to forecast customer churn for a telecommunications company, achieving 92% accuracy.
Tools/Tech: Python, Pandas, NumPy, SciPy, Scikit-Learn, TensorFlow, Keras, Streamlit

Built a forecasting model to predict sales for the next 14 days with an error rate below 5%, based on multi-mall consumer behavior and shopping data.
Tools/Tech: Tableau, Python, Pandas, NumPy, SciPy

• 🎓 Management graduate shifting career to Data Analytics & Data Science
• 💡 Strong focus on delivering business-driven insights, not just technical solutions
• 🚀 Building a diverse portfolio while preparing for Data Analyst / Data Science opportunities
• 📚 Actively learning ML, Data Visualization, and BI Tools

Let’s connect and talk about data, analytics, or exciting new projects!