Abdishakur Yoonis

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Abdishakur Yoonis


MSc Data Scientist
MSc Software Engineer
BSc Software Engineer
Data Science
Data Analysis
Artificial intelligence (AI)
Machine Learning
Data Engineering
Business Intelligence
Software Engineering
Software Development
Python, R, SQL, C#, Java, JavaScript and many more
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Abdishakur Yoonis

Abdishakur.Yoonis@ba.com | 07306445649
Slough, Berkshire, UK
LinkedIn | GitHub | Portfolio

SKILLS

  • Programming Languages: Python, R, SQL, Java, C#, C++, HTML, CSS, JavaScript and many more
  • OS: Windows, Linux (Ubuntu 18.04)
  • Shell: PowerShell, Bash
  • Databases: Microsoft SQL Server - (SSMS), PostgreSQL, Oracle SQL and Amazon Redshift
  • NoSQL: MongoDB, Cassandra and Amazon DynamoDB
  • Cloud Computing: AWS and AZURE
  • Business Intelligence and Data Visualisation: Microsoft Power Bi, SQL, Microsoft Dynamics CRM, Advanced Excel, VBA, Tableau and Qlik
  • Frameworks/Libraries: Pandas, NumPy, SciPy, Statsmodels, Pyspark, Sci-kit Learn, Tensorflow, Keras, NLTK, Gensim, Matplotlib, Seaborn, Plotly, Flask
  • Technical Skills: Data Collection, Data Wrangling/Cleaning, Exploratory Data Analysis (EDA), Hypothesis Testing, Statistical Analysis, Deep Learning, Machine Learning, Regression, Classification, Clustering, Version Control (Git)

DATA SCIENCE PROJECTS

Sparkify Churn: Capstone Project | Project Link

Apr 2022
  • Loading and cleaning a small subset (128MB) of a full dataset available (12GB).
  • Conducting Exploratory Data Analysis to understand the data and what features are useful for predicting churn.
  • Feature Engineering to create features that will be used in the modelling process.
  • Modelling using machine learning algorithms such as Logistic Regression, Random Forest, Gradient Boosted Trees, Linear SVM, Naive Bayes

Disaster Response | Project Link

Feb 2022
  • Utilized frameworks such as NLTK and Scikit-Learn to perform ETL, build ML pipeline, and deploy ML model to a local web application.
  • The ML pipeline processes 26,000 raw text messages using NLTK and Scikit-Learn to build a multioutput classification model.
  • Maximized F1 score through feature engineering and parameter tuning.

Communicate Data Finding | Project Link

May 2021
  • I will investigate Ford GoBike System Dataset, assess its quality and tidiness, then clean it which called data wrangling
  • Ford GoBike System Dataset includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area.
  • Most users are Subscribers
  • Subscribers have the lowest number of trips in the weekend holiday (Saturday and Sunday) while Customers have the lowest number of trips on Wednesday and have realtively better numbers of trips in the weekend holiday (Saturday and Sunday).
  • Most of trips are taking less than 15 mins and the top number of the trips takes about 10 mins.
  • Subscribers have narrower trip duration than Customers
  • Subscibers have more specific Trips than casual Customers
  • Most users are Subscribers and Dominant gender is Male
  • User with Age between 25 and 35 are making top of number of trips

EXPERIENCE

Ground Operations Agent, British Airways, Heathrow Airport – T5, UK

JUNE 2024 – Present
  • Physical fitness to handle manual tasks, including lifting items up to 32kg
  • Preparing aircraft for arrival, departure, and turnaround activities
  • Loading and unloading customer baggage, cargo and approved items onto the aircraft
  • Delivery of customer baggage to designated collection/drop-off points
  • Identifying continuous improvement opportunities and contributing to a safe, secure, and effective customer baggage operation at LHR
  • Responsible for the on-the-day delivery of turnaround activities, including baggage handling at LHR

Data Scientist/Data Analyst (Volunteer), MSI Homes Group, Bristol, UK

OCT 2019 – NOV 2021
  • To predict house prices using time series analysis and neural networks.
  • Identify factors that predict which employees will have the best performance and which will benefit from a change in their job position using machine learning.
  • Designed the information architecture and model of an organization’s assets.
  • Coordinated with the stakeholders on project progress.
  • Involved in the continuous enhancements and finding the best solution.

EDUCATION

  • MSc Software Engineering, Kingston University, Oct 2018
  • BSc Software Engineering, London Metropolitan University, Jul 2017
  • Microsoft Certified Software Developer, Microsoft UK – Certificate, Feb 2014
  • Exploratory Data Analysis in Excel, LinkedIn Learning – Certificate, 2018
  • Exploratory Data Analysis in SQL, Datacamp – Certificate, 2019
  • Introduction to SQL Server, Datacamp – Certificate, 2019
  • Intermediate to SQL Server, Datacamp – Certificate, 2019
  • Introduction to Relational Databases in SQL, Datacamp – Certificate, 2019
  • Pandas and Jupyter Notebook, Datacamp – Certificate, 2019
  • Data Engineering, Datacamp – Certificate, 2019
  • Machine Learning and Deep Learning, Datacamp – Certificate, 2019
  • Python 3 Programming, Coursera – Certificate, May 2019
  • Data Science - Specialisation at John Hopkins University, Coursera – Certificate, Sep 2019
  • Big Data - Specialisation at UC San Diego, Coursera – Certificate, Jan 2020
  • Data Analysis Nanodegree, Udacity – Certificate, Jun 2021
  • Data Science Nanodegree, Udacity – Certificate, April 2022
  • AWS Machine Learning, Udacity – Certificate, Aug 2021
  • Cleaning Data With Pyspark, Datacamp – Certificate, 2022
  • Introduction To Pyspark, Datacamp – Certificate, 2022
  • Data Analyst In Power BI, Datacamp – Certificate, 2022
  • Introduction To Power BI, Datacamp – Certificate, 2022
  • Introduction To DAX in Power BI, Datacamp – Certificate, 2022
  • Data Visualization In Power BI, Datacamp – Certificate, 2022
  • Data Analyst Diploma, Pitman Training – Certificate, 2023

Download Resume here