Abdul Rehman
New York City,NY
Summary
Accomplished data analyst and scientist with experience in data-driven strategy development, predictive modeling, and advanced analytics. Proficient in Python (Pandas, NumPy, Scikit-learn), machine learning algorithms, and data visualization. Demonstrated success in optimizing inventory management, conducting customer behavior analysis, and enhancing operational efficiency. Adept at leveraging data insights to inform strategic decision-making and drive business growth. Strong collaborator with cross-functional teams to integrate analytics solutions and deliver actionable insights for improved quality control and targeted marketing strategies.
Overview
6
6
years of professional experience
1
1
Certification
Work History
New Business Consultant
Advanced
06.2022 - 03.2024
- Led data-driven business development strategies, boosting client satisfaction by 15% in six months through actionable insights
- Employed advanced analytics tools and techniques to uncover market trends and identify growth opportunities
- Created predictive models with 85% accuracy, enhancing operational efficiency by 20% through data-driven forecasts
- Partnered with cross-functional teams to integrate analytics solutions into core business processes and decision-making frameworks
- Increased client acquisition rates by 25% through Python-based web scraping (BeautifulSoup) and data-driven lead generation.
Data Analyst
Sam Carpets
02.2022 - 07.2022
- Utilized SQL, Python, and Excel for comprehensive data analysis and visualization, enhancing decision-making processes
- Created and implemented inventory management dashboards in Excel, optimizing stock levels and reducing holding costs
- Delivered actionable insights on customer preferences and purchasing patterns, leading to improved marketing strategies.
Study
01.2021 - 02.2022
Pursuing my Postgraduate.
Supply Chain Analyst
Fauji Foods Limited
08.2019 - 12.2020
- Reduced excess inventory holding costs by 10% through data-driven optimization of inventory levels and minimization of stockouts
- Analyzed supply chain data to streamline procurement processes and enhance inventory turnover ratios
- Implemented KPI dashboards, achieving a 15% reduction in procurement cycle times by monitoring and improving key supply chain metrics
- Conducted root cause analysis of supply chain disruptions and executed corrective actions to enhance supply chain resilience
- Developed and leveraged advanced analytics to identify cost-saving opportunities and improve supply chain efficiency.
Intern
Fauji Foods Limited
05.2018 - 09.2018
- Assisted in data collection and analysis for supply chain optimization projects, contributing to actionable process improvement recommendations
- Supported the implementation of inventory management strategies, reducing holding costs and enhancing inventory turnover ratios
- Participated in cross-functional meetings and workshops, gaining comprehensive exposure to various aspects of supply chain management and operations
- Collaborated with procurement and logistics teams to streamline operations, resulting in improved efficiency and cost savings
- Developed and maintained KPI dashboards to monitor supply chain performance and identify areas for continuous improvement.
Education
Master of Science - Business Management And Analytics
University of Aberdeen
02.2022
Bachelor of Science - Management Science
Lahore University of Management Sciences
05.2019
Skills
- Data Analysis
- Machine Learning
- Predictive Modeling
- Python (Pandas, NumPy, Scikit-learn)
- Data Preprocessing
- Feature Engineering
- Data Visualization
- Inventory Management Optimization
- Customer Behavior Analysis
- Strategic Decision-Making
- Cross-Functional Collaboration
- Quality Control Improvement
- Marketing Strategy Development
- Data Wrangling
- Statistical Analysis
- SQL (MS SQL Server, Oracle, MySQL)
- R Programming
- Advanced Microsoft Excel
- Web Scraping (BeautifulSoup, Requests)
- Time Series Forecasting
- Neural Networks (TensorFlow, Keras)
- Regression Analysis
- Clustering Techniques
- Process Improvement
- Financial Analysis
- Budgeting
- Risk Management
- Project Management
- Communication
- Problem-Solving
- Critical Thinking
- Teamwork
- Leadership
- Time Management
- Adaptability
Projects
- Customer Churn Analysis - EDA and Logistics Regression.
Conducted a comprehensive churn analysis for a telecommunications company using Python (Pandas, NumPy, Matplotlib), employing univariate and bivariate analysis to identify key customer characteristics, and developed a high-accuracy predictive neural network model (Tensorflow, Keras) to provide strategic recommendations based on findings.
- Bitcoin Price Movement - Sentiment Analysis & Xgboost.
Extracted Bitcoin data using Python (Mwclient, Yfinance) and conducted predictive analysis with XBoost, achieving 70% accuracy in forecasting price movements through feature engineering.
- E-Commerce Marketplace Analysis - Using Web Scraping to Identify Profitable Product Opportunities.
Scraped and analyzed product trends on Daraz(Pakistan's largest e-commerce platform) using Python (BeautifulSoup, Requests) to provide actionable insights for product selection, aiding in strategic decision-making.
- Traffic Sign Recognition System - using Convoluted Neural Networks.
Developed a traffic sign recognition system using CNNs in Python (Keras, TensorFlow), achieving 96% accuracy and surpassing standard neural network performance.
- Customer Segmentation Using K-Means.
Performed K-means clustering on customer data using Python (Pandas, Scikit-learn, Matplotlib) to identify distinct segments, analyze behavior patterns, and develop targeted marketing strategies, enhancing customer retention and acquisition efforts.
- Used Car Price Prediction - Polynomial Regression.
Developed a polynomial regression model to predict used car prices with over 92% accuracy using Python (Pandas, NumPy, Scikit-learn) for data pre-processing and model training, implemented feature engineering techniques, and provided actionable insights for pricing strategies and market analysis.
- Steel Plate Defect Detection - Random Forest Classifier.
Used a Random Forest Classifier with Python (Pandas, Scikit-learn) for data preprocessing, model training, and evaluation to detect defective steel plates with 88% accuracy, enhancing model accuracy through feature selection and engineering, and delivering insights to improve quality control processes in manufacturing.
Certification
- Microsoft Excel - ADVANCED Certificate | Reed.co.uk
- Google Data Analytics Certificate | Google
- SQL for Data Science | University of California, Davis
- Python for Data Science, Al, and Development | IBM
- Python Programming | University of Helsinki
- Google Advanced Data Analytics | Google
- Supervised Machine Learning: Regression and Classification | Stanford University
- Python programming CSSOP | Harvard University
- Advanced Learning Algorithms | Stanford University
- Introduction to Computer Science CS50X | Harvard University
References
References available on request.
Timeline
New Business Consultant
Advanced
06.2022 - 03.2024
Data Analyst
Sam Carpets
02.2022 - 07.2022
Study
01.2021 - 02.2022
Supply Chain Analyst
Fauji Foods Limited
08.2019 - 12.2020
Intern
Fauji Foods Limited
05.2018 - 09.2018
Master of Science - Business Management And Analytics
University of Aberdeen
Bachelor of Science - Management Science
Lahore University of Management Sciences