Sumer Pasha

About Me

Data Analyst and Python Automation Engineer with 2 year of experience in automating workflows, data analysis, and visualization. Proficient in SQL, Python, and ETL processes to extract, transform, and load data into structured systems for analysis. Skilled in creating interactive dashboards and building automation solutions to optimize business operations. Adept at using Python for data-driven insights, improving processes, and driving efficiency.

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Profile Summary

  • Experienced Data Analyst: Over 1 year of experience in data analysis, automation, and visualization, delivering actionable insights to enhance business operations and decision-making.

  • Technical Expertise: Proficient in Python, SQL, R, and ETL processes, with a strong focus on data cleaning, modeling, and structuring for efficient querying and analysis.

  • Automation Skills: Developed Python-based automation solutions, including email campaigns and invoicing systems, reducing manual workloads and improving efficiency.

  • Visualization Proficiency: Skilled in creating interactive dashboards using Power BI and Matplotlib to monitor KPIs, trends, and performance metrics, improving decision-making efficiency.

  • Machine Learning Foundations: Hands-on experience in implementing supervised and unsupervised learning models using Scikit-Learn, deriving predictive insights from complex datasets.

  • Possess strong database management skills, optimizing data storage and retrieval efficiency with MySQL and MongoDB.

Technical Skills

Python
SQL
ETL & EDA
MongoDB
Power BI
Seaborn
Machine Learning
Scikit-Learn
R
Git
GitHub
Statistics
Data Visualization
Data Processing
PySpark
Web Scraping

Internships

Python Automation Engineer

Analogica Software Dev Pvt Ltd, Bengaluru, Karnataka

06/2022 – 01/2023

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Professional Experience

Data Analyst & Python Automation Engineer

Analogica Software Dev Pvt Ltd

03/2023 – Present

  • Developed Python scripts for automating data collection and cleaning, saving 15+ hours per week and ensuring data consistency.
  • Built SQL-based ETL pipelines to manage and structure data for analysis, improving data processing time by 30%.
  • Designed interactive Power BI dashboards for tracking KPIs and business trends, enhancing decision-making efficiency by 25%.
  • Conducted exploratory data analysis (EDA) to uncover actionable insights that informed business strategy and improved operational efficiency by 19%.
  • Automated mass email campaigns and invoicing using Python, reducing manual workload by 40%.

Certificates

  • Scala Programming for Data Science.
  • Diploma in Machine Learning & AI.
  • Data Analytics with Python & SQL.
  • Data Visualization: Empowering Business with Effective Insights.

Projects

Crop & Fertilizer Recommendation System.

Developed a Flask-based web application that predicts the optimal crop to grow based on soil and weather conditions and recommends the right fertilizer for a healthier yield using a Random Forest Classifier.

  • Tools Used: Python, Tkinter, Pandas, scikit-learn, Numpy, Flask, Render.
  • Implemented a machine learning model integrated with a Python backend and deployed the solution on Render Cloud.
  • Planned future enhancements include integrating a real-time weather API for dynamic predictions, deploying on AWS SageMaker for scalability, and expanding to a mobile app version.

Live App: https://agriculture-pridiction.onrender.com/

GitHub Repo: https://github.com/1sumer/Agriculture_Pridiction

Global Superstore Sales Profitability Analysis.

Analyzing the sales performance and profitability across regions and product categories in the Global Store dataset provides key insights for business strategy and growth.

  • Tools Used: SQL, Python, Power BI, Pandas, Numpy
  • Analyzed sales, profitability, and shipping dynamics to deliver actionable insights for improving customer satisfaction and operational efficiency.
  • Built visualizations to identify high-performing products, regions, and customer segments, enabling data-informed decision-making.

IMDb Movie Recommender System

An IMDb Movie Recommender System that suggests personalized movie recommendations based on user preferences and ratings.

  • Tools Used: Python, Scikit-Learn, Pandas, NumPy, Statistics.
  • Improved user experience by delivering personalized movie recommendations based on user behavior and movie attributes.

Automated Bulk Email Sender Using SMTP Server

Mass Emailer is a Python-based application designed to send bulk emails efficiently using an SMTP server.

  • Bulk Email Sending: Facilitate the sending of large numbers of emails simultaneously.
  • User-Friendly Interface: Utilize Tkinter to create an intuitive and accessible GUI.
  • SMTP Integration: Seamlessly connect with SMTP servers to handle email delivery.

06/2024

E-Commerce Data Extraction and Analysis

Automating the extraction and analysis of e-commerce data for actionable insights.

  • Tools Used: Python (BeautifulSoup, Pandas), Power BI.
  • Scraped and analyzed product data from e-commerce platforms to identify pricing trends and market positioning.
  • Delivered insights that aided competitive strategy formulation.

Blogs

Python’s Oop's Revolution

Explored how Python’s Object-Oriented Programming (OOP) features simplify code organization, enhance reusability, and support scalable application development.

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The Importance of SQL in Today's World: A Fundamental Data Manipulation Language

Highlighted the critical role of SQL in modern data management, showcasing its applications in querying, data manipulation, and supporting data-driven decision-making.

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Exploring the Core Principles of Decision Tree in Machine Learning

Decision trees in machine learning are a predictive modeling tool that splits data into branches based on feature values to make decisions or predictions. They work by recursively partitioning the dataset into subsets, aiming to maximize information gain or minimize impurity at each split.

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