Amir Saleem

Data Scientist and Python Developer with 6+ years of experience in data analysis, data engineering, and machine learning. Proven ability to transform raw data into actionable insights using data wrangling, feature engineering, and predictive modeling. Proficient in Python and SQL. Passionate about solving complex problems using data-driven approaches. Certified in data analysis, programming, machine learning, and data engineering.

Experience

Python Data Scientist

Turing
Remote (USA)

Nov 2023 - Present

  • Currently working on an LLM with millions of users: Gather data, formulate complex questions, develop code solutions, and collaborate with the LLM to enhance its capabilities by identifying errors and providing feedback.
  • Engage in collaborative data analysis, independently explore datasets, and craft complex inquiries covering EDA, statistics, ML, logic, and open-ended questions.
  • Develop code solutions and collaborate with colleagues to compare and validate results. Identify and flag questions with code solutions to refine LLM training, enhancing accuracy and performance.

Data Engineer ( Freelancer )

Medusa
Remote (USA)

Jun 2023 - Feb 2024
(9 months)

  • Implemented ETL processes using Redshift, Athena, and MySQL on AWS Lambda functions within Docker containers.
  • Incorporated existing CI/CD pipelines via Bitbucket to enable smooth code deployment processes.
  • Executed code pushes to trigger Bitbucket pipelines for automated builds.
  • Managed Docker image deployments to AWS and monitored performance via CloudWatch.
  • Implemented reverse ETL processes for Monday.com utilizing GraphQL with their API.

Data Scientist

LoveForData
On-site (Karachi - Pakistan)

Jan 2023 - Nov 2023
(11 months)

  • Conducting data analysis, data mining, and modeling to extract insights and support decision-making processes.
  • Collaborating with cross-functional teams to define project objectives and deliver actionable recommendations.
  • Designing and deploying data pipelines and workflows to process and analyze datasets.

Data Analyst

LoveForData
On-site (Karachi - Pakistan)

Jan 2021 - Dec 2022
( 2 years )

  • Gathered, cleansed, and analyzed data from various sources to identify patterns and trends.
  • Conducted statistical analysis and hypothesis testing to derive meaningful conclusions.
  • Collaborated with team members to develop data-driven strategies and recommendations.
  • Assisted in the development and maintenance of data analytics tools and infrastructure.

Junior Data Analyst

LoveForData
On-site (Karachi - Pakistan)

Apr 2019 - Dec 2020
( 1 year, 9 months )

  • Assisted in data collection, cleaning, and validation processes.
  • Conducted basic data analysis and generated descriptive reports.
  • Supported senior analysts in data visualization and report creation.
  • Collaborated with team members to enhance data quality and accuracy.
  • Assisted in the implementation and maintenance of data management systems.

Data Science Trainee

LoveForData
On-site (Karachi - Pakistan)

Oct 2018 - Mar 2019
( 6 months )

  • Participated in hands-on training in data analysis, machine learning, and data visualization.
  • Assisted in data preprocessing and feature engineering tasks.
  • Contributed to exploratory data analysis and insights generation.
  • Learned and applied best practices in data science and analytics.

Data Science Intern

LoveForData
On-site (Karachi - Pakistan)

Aug 2018 - Sep 2018
( 2 months )

  • Assisted in data collection, cleaning, and organization.
  • Gained exposure to various data analysis tools and techniques.

Certifications

55- SQL (Intermeidate)

hackerrank
Issued: June 2023

Verify

54- SQL (Basic)

hackerrank
Issued: June 2023

Verify

53- Fundamentals of Visualization with Tableau

University of California, Davis
Issued: May 2023

Verify

52- Essential Design Principles for Tableau

University of California, Davis
Issued: May 2023

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51- Visual Analytics with Tableau

University of California, Davis
Issued: May 2023

Verify

50- Python (Basic)

Hackerrank
Issued: Feb 2023

Verify

49- Introduction to Big Data with Spark and Hadoop

IBM Skills Network
Issued: Dec 2022

Verify

48- Python for Data Science, AI & Development

IBM Skills Network
Issued: Nov 2022

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47- Python Project for Data Engineering

IBM Skills Network
Issued: Nov 2022

Verify

46- Databases and SQL for Data Science with Python

IBM Skills Network
Issued: Nov 2022

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45- Hands-on Introduction to Linux Commands and Shell Scripting

IBM Skills Network
Issued: Nov 2022

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44- Relational Database Administration (DBA)

IBM Skills Network
Issued: Nov 2022

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43- ETL and Data Pipelines with Shell, Airflow and Kafka

IBM Skills Network
Issued: Nov 2022

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42- Getting Started with Data Warehousing and BI Analytics

IBM Skills Network
Issued: Nov 2022

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41- Introduction to NoSQL Databases

IBM Skills Network
Issued: Nov 2022

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40- Introduction to Statistics

Stanfor University
Issued: Oct 2022

Verify

39- How Google does Machine Learning

Google Cloud
Issued: Oct 2022

Verify

38- Google Cloud Big Data and Machine Learning Fundamentals

Google Cloud
Issued: Oct 2022

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37- Introduction to Data Engineering

IBM Skills Network
Issued: Oct 2022

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36- Introduction to Relational Databases (RDBMS)

IBM Skills Network
Issued: Oct 2022

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35- Google Data Analytics (Professional Certificate)

Google
Issued: Sep 2022

Verify

34- Foundations: Data, Data, Everywhere

Google
Issued: Aug 2022

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33- Share Data Through the Art of Visualization

Google
Issued: Aug 2022

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32- Ask Questions to Make Data-Driven Decisions

Google
Issued: Aug 2022

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31- Prepare Data for Exploration

Google
Issued: Aug 2022

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30- Data Analysis with R Programming

Google
Issued: Aug 2022

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29- Google Data Analytics Capstone: Complete a Case Study

Google
Issued: Aug 2022

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28- Process Data from Dirty to Clean

Google
Issued: Aug 2022

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27- Python Project: pillow, tesseract, and opencv

University of Michigan
Issued: Oct 2021

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26- Python 3 Programming (Specialization)

University of Michigan
Issued: Oct 2021

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25- Introduction to Probability and Data with R

Duke University
Issued: Oct 2021

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24- Using Python to Access Web Data

University of Michigan
Issued: Sep 2021

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23- Using Databases with Python

University of Michigan
Issued: Sep 2021

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22- Capstone: Retrieving, Processing, and Visualizing Data with Python

University of Michigan
Issued: Sep 2021

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21- Python Basics

University of Michigan
Issued: Sep 2021

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20- Data Collection and Processing with Python

University of Michigan
Issued: Sep 2021

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19- Python Functions, Files, and Dictionaries

University of Michigan
Issued: Sep 2021

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18- Python Classes and Inheritance

University of Michigan
Issued: Sep 2021

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17- Python for Everybody (Specialization)

University of Michigan
Issued: Sep 2021

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16- Programming for Everybody (Getting Started with Python)

University of Michigan
Issued: Aug 2021

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15- Python Data Structures

University of Michigan
Issued: Aug 2021

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14- Linux for Developers

The Linux Foundation
Issued: Nov 2020

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13- Linux Server Management and Security

University of Colorado System
Issued: Oct 2020

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12- Analyzing Police Activity with pandas

datacamp
Issued: Sep 2020

Verify

11- Introduction to Applied Machine Learning

Alberta Machine Intelligence Intitute
Issued: Jan 2020

Verify

10- Machine Learning Algorithms: Supervised Learning Tip to Tail

Alberta Machine Intelligence Intitute
Issued: Jan 2020

Verify

9- Data for Machine Learning

Alberta Machine Intelligence Intitute
Issued: Jan 2020

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8- R Programming

John Hopkins University
Issued: Aug 2019

Verify

7- Exploratory Data Analysis

John Hopkins University
Issued: Aug 2019

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6- Getting and Cleaning Data

John Hopkins University
Issued: Jul 2019

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5- The Data Scientist’s Toolbox

John Hopkins University
Issued: Jun 2019

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4- Excel Skills for Business: Essentials

Macquarie University
Issued: Aug 2018

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3- Excel Skills for Business: Intermediate I

Macquarie University
Issued: Aug 2018

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2- Introduction to Data Science in Python

University of Michigan
Issued: Apr 2018

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1- Learn to Program: The Fundamentals

University of Toronto
Issued: Dec 2017

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Skills

  • Data Science: Experience in data analysis, data mining, modeling, and deploying data pipelines.
  • Machine Learning: Developing predictive models and implementing machine learning algorithms.
  • Data Analysis: Gathering, cleaning, and analyzing data to extract insights and support decision-making.
  • Python Programming: Proficient in Python for data analysis, scripting, and automation tasks.
  • R Programming: Good in R for data analysis, and ML modeling.
  • SQL: Skilled in querying and managing relational databases.
  • ETL Processes: Designing and implementing Extract, Transform, Load processes for data integration.
  • Linux: Experience working in Linux environments, including scripting and system management.
  • Django: Developing web applications using the Django framework.
  • Bash Scripting: Automating tasks and managing systems using Bash scripts.
  • Data Visualization: Creating visual representations of data to communicate insights effectively.
  • Web Scraping: Extracting data from websites using tools like BeautifulSoup.
  • Cloud Computing: Utilizing cloud services, including Azure Functions, for scalable computing solutions.
  • Version Control: Managing code versions and collaboration using Git.

    • Professional Projects

    Egypt-Pakistan-Phone-Data

    BeautifulSoup

    Scraped used and new mobile's data from 10 different websites for Egypt and Pakistan, using BeautifulSoup.
    Demonstrated the ability to fetch data using BeautifulSoup.

    Analysis of 1 million repos metadata

    GITHUB SEARCH API • PANDAS • SEABORN • MATPLOTLIB

    Fetched data for the last one million Github repositories created, using Github Search API, then analyzed the data using Pandas, Matplotlib, and Seaborn. Created multiple charts and summaries.
    Demonstrated the ability to fetch data using an API and perform data analysis using Python.

    ETL Pipeline

    ETL • PYTHON • SQL • MySQL • LINUX

    Worked on a Data Engineering project for a client with a mobile application used by thousands of users. The app was collecting daily data from devices in .txt format, ziping the files, and sent them to a server. I was given access to these files and developed an ETL process to handle them at scale. For each zip file, I extracted information from messy .txt files, fetched user data from relevant tables, and updated or created new rows based on multiple conditions. This process was executed daily for thousands of .zip files. I successfully built and deployed the solution on a Linux server, ensuring efficient data processing, accuracy, and seamless integration with existing systems.

    Reverse ETL Pipeline

    REVERSE ETL • GraphQL • API • LINUX • PYTHON

    Implemented Data Engineering processes, specifically reverse ETL, for Monday.com utilizing GraphQL with their API. The script was to fetch data for the last 24 hours from Monday.com and load it into MySQL tables. Deployed the script on a Linux server using a cron job, ensuring automated, reliable, and efficient data synchronization.

    ETL Pipeline

    ETL, Redshift • Athena • MySQL • Slack • Bitbucket • Docker • AWS • CloudWatch

    Implemented Data Engineering processes by writing multiple ETL scripts to fetch data from Redshift, Athena, and MySQL, run checks, and send messages to a Slack bot if any check fails. Incorporated existing CI/CD pipelines via Bitbucket for smooth deployments. Executed code pushes to trigger Bitbucket pipelines for automated builds. Managed Docker image deployments to AWS and monitored performance via CloudWatch, ensuring reliability, scalability, and efficient system monitoring.

    "Multi-Source Property Data Scraper"

    WEB-SCRAPING • BeautifulSoup

    Developed a web scraping script to collect data from diverse online sources. The code structure, organized into the 'scraper_class,' featured nested classes and methods for efficient data extraction.
    Using Python librariey BeautifulSoup, I retrieved property listing data, both for buying and renting, storing it in formats such as pickle files and CSV.
    This project highlights my web scraping skills and proficiency in data extraction and manipulation for various online platforms.

    EDA and Machine Learning Application

    DJANGO • REST API • PANDAS • SEABORN

    Developed a comprehensive Django application encompassing extensive Exploratory Data Analysis (EDA), advanced Machine Learning (ML) models creation, and insightful market basket analysis. Leveraged strong programming skills and data science expertise to build a robust and interactive platform, enabling in-depth data exploration, accurate predictive modeling, and valuable market insights.
    Demonstrated ability to integrate multiple analytical techniques into a unified application, enhancing data-driven decision-making capabilities.

    ETL

    ETL • MYSQL • PYTHON

    Designed and implemented a robust Extract, Transform, Load (ETL) script to efficiently process and integrate large volumes of data into a MySQL database. Employed manual parsing techniques and applied sophisticated logic to extract relevant information, ensuring data accuracy and consistency. Developed intricate data transformation rules and efficiently loaded the processed data into multiple tables, enabling seamless data retrieval and analysis. Demonstrated strong problem-solving skills and attention to detail in handling complex data structures and delivering a streamlined ETL workflow.

    Car Price Estimation

    Machine Learning • REGRESSION

    Developed a machine learning model to accurately predict car prices based on various factors such as brand, model, year of manufacture, mileage, and other relevant features. Gathered and preprocessed a large dataset of car listings, performed feature engineering, and applied advanced regression techniques to build a robust pricing model. Achieved high accuracy in predicting car prices, enabling informed decision-making for buyers and sellers in the automotive market. This project showcased expertise in data analysis, feature engineering, and regression modeling, highlighting the ability to deliver valuable insights and drive business outcomes in the automotive industry.

    Dynamic Hiring Portal for Streamlined Assessments

    DJANGO • REST API • PYTHON • MYSQL

    Developed a dynamic Django application for candidate hiring, streamlining the assessment process and enhancing the candidate experience. Implemented a secure user registration system, where candidates receive personalized login credentials via email to access the portal. Leveraged Django's flexible architecture to create a question bank with randomized selection based on the candidate's department, ensuring a tailored assessment experience. Incorporated multiple difficulty levels to accurately evaluate candidate skills and knowledge. Implemented automatic time tracking and submission features, providing a seamless assessment experience for candidates. Developed email notification functionality to inform both candidates and HR personnel of assessment completion or time expiration, facilitating efficient communication throughout the hiring process. Demonstrated strong problem-solving abilities and attention to detail in delivering a user-friendly and efficient hiring portal.

    Loan Default Pprediction

    MACHINE LEARNING • PYTHON

    Built a highly accurate loan default prediction model, achieving an exceptional AUC score of 0.88. Demonstrated expertise in data analysis and predictive modeling, enabling proactive customer retention strategies. Highlighted strong analytical skills and data-driven decision-making.

    Data Audit

    MYSQL • PYTHON

    Conducted a comprehensive data audit, identifying and addressing multiple data inconsistencies, and errors, resulting in improved data quality, streamlined processes, and enhanced decision-making capabilities.

    Web Scraping

    WEB SCRAPING • PYTHON • SQLITE

    Coordinated with a highly skilled team to develop, and deploy a comprehensive suite of 200+ Python web scraping scripts. These scripts demonstrated exceptional versatility and adaptability, enabling the extraction of critical data from a wide range of websites and contributing to the team's success in project deliverables.

    Predicting Customer Lifetime Value

    Machine Learning • R

    Built a machine learning model to forecast customer lifetime value in the telecommunications industry. Utilized historical data and advanced techniques to accurately predict long-term customer value, enabling targeted marketing and improved customer retention. Demonstrated expertise in data analysis, predictive modeling, and driving business growth through data-driven strategies.

    Land Price Prediction

    Machine Learning • ORACLE SQL • PYTHON

    Developed and deployed a highly accurate land price prediction model using machine learning algorithms. Leveraging my expertise in data analysis, feature engineering, and predictive modeling, I created a robust solution that accurately predict land prices based on relevant factors such as location, and property attributes. This model not only provided valuable insights for real estate professionals but also contributed to informed decision-making and improved profitability in the industry.

    R-shiny Dashboard

    R-shiny • Dashboard • R

    Built a dashboard using R-shiny

    NLP

    MongoDB • Python • NLP

    NLP Sentiment Analysis for TV Show Comments: Developed an NLP solution to analyze comments about TV shows and classify them as positive or negative sentiments. Demonstrated expertise in text mining, sentiment analysis, and machine learning, providing valuable insights into audience preferences and feedback in the entertainment industry.

    Coding Profiles

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