I will clean your dataset and deliver actionable business insights
Data Scientist, AI Solutions Engineer, Agentic AI Specialist
About this Gig
๐๐ฌ ๐ฒ๐จ๐ฎ๐ซ ๐ซ๐๐ฐ ๐๐๐ญ๐ ๐ก๐จ๐ฅ๐๐ข๐ง๐ ๐๐๐๐ค ๐ฒ๐จ๐ฎ๐ซ ๐๐ฎ๐ฌ๐ข๐ง๐๐ฌ๐ฌ ๐๐๐๐ข๐ฌ๐ข๐จ๐ง๐ฌ?
Poor data quality leads to wrong insights, failed models, and wasted time. I turn your messy, unstructured dataset into clean, analysis-ready data with clear business insights you can act on immediately.
๐๐ก๐๐ญ ๐ ๐๐๐ฅ๐ข๐ฏ๐๐ซ:
1. ๐๐ซ๐จ๐๐๐ฌ๐ฌ๐ข๐จ๐ง๐๐ฅ ๐๐๐ญ๐ ๐๐ฅ๐๐๐ง๐ข๐ง๐
Remove duplicates, fix missing values, and correct formatting errors
Detect and treat outliers to prevent skewed results
Standardize data types and structure for accuracy
2. ๐๐ฑ๐ฉ๐ฅ๐จ๐ซ๐๐ญ๐จ๐ซ๐ฒ ๐๐๐ญ๐ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ข๐ฌ (๐๐๐)
Uncover trends, patterns, and correlations hidden in your data
Identify which variables actually impact your business outcomes
Visualize key insights with clear, professional charts
3. ๐ ๐๐๐ญ๐ฎ๐ซ๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ๐ข๐ง๐
Encode, scale, and transform variables for ML readiness
Create new meaningful features from existing columns
Deliver a fully model-ready dataset
๐๐ก๐ฒ ๐๐จ๐ซ๐ค ๐๐ข๐ญ๐ก ๐๐:
Final year AI Engineering student with real project experience
Delivered analysis on 1,500+ row real-world datasets
Clean, documented Python code using Pandas, Seaborn
My Portfolio
FAQ
What do I need to provide to get started?
Please provide your dataset in CSV, Excel, or SQL format along with a brief description of your goals. If you have specific questions you want the Exploratory Data Analysis (EDA) to answer, feel free to list them!
Which tools do you use for data cleaning and EDA?
I primarily use Python with powerful libraries like Pandas and NumPy for data manipulation, and Matplotlib or Seaborn for high-quality data visualizations.
Can you handle very messy datasets with missing values?
Yes! That is my specialty. I use advanced imputation techniques (mean, median, mode, or predictive filling) and outlier detection to ensure your data is consistent and ready for analysis.
What is "Feature Engineering" and why do I need it?
Feature Engineering is the process of creating new variables from your raw data to help Machine Learning models perform better. For example, turning a "Date" column into "Day of the Week" or "Is Holiday." It adds significant value to your predictive models.
What does "100 Items Cleaned" refer to in your packages?
In the Data Cleaning category, Fiverr sets a minimum of 100 items. I treat these "items" as data points or rows. My Basic package is designed to provide high-quality cleaning and EDA for standard datasets. If your file has several thousand rows, don't worryโI can handle it within the listed package
Will I get the source code?
Absolutely. I will deliver a well-documented Jupyter Notebook (.ipynb) or Python script so you can see exactly how the data was transformed and recreated in the future.
Is my data safe with you?
Yes, I take data privacy very seriously. Your data will only be used for the scope of the project and will be deleted from my system once the order is completed and accepted.

