United States

Data Engineering

Data Scientist

Data Analysis

GCE Advanced Level and GCE Ordinary Level

Moiz Sadiq Awan

Business Intelligence Engineer

Communication

Collaboration

Problem-solving

Critical-thinking

Analytical skills

Python

Tableau

Apache Spark

ChatGPT

Pandas

Google Data Studio

PostgreSQL

Jupyter Notebook

Keras

Matlab

Matplotlib

Numpy

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Amazon Music - Alexa on Mobile, App Stability & Performance, Exec Reporting

• Managed tasks related to Business Analytics and Extract Transform Load (ETL) for NOS (Portugal) Telesales and Retention queues and YapiKredi (Turkey) Telesales queue, helping all three queues achieve target gains of 5%, 7% and 8% respectively. 
• Led tasks based on data join procedures, data pipelines, ad-hoc analyses, drafting of new business cases, feature engineering and reconciliation with client.
• Calculated Customer Lifetime Value for Retention queue and churn scores for ‘Retained Without Change in Contract’ metric. 
• Automated ETL processes, reducing execution time of daily processes by over 50%.
• Trained fresh resources on both accounts by conducting knowledge transfer sessions.
• Tools/Technologies: SQL, Python, R, Talend, NumPy, Pandas, Matplotlib, Seaborn, Microsoft Excel

• Built a hybrid model that predicts human egg fertilization and blastocyst embryo development using image data and clinical factors of patients with 77% accuracy and 62% accuracy respectively using Machine Learning and Deep Learning Techniques. 
• Conducted research and development on Class Imbalance, Image Preprocessing, Custom Loss Functions and Optimizers, Ensemble Learning and Bayesian Hyperparameter Optimisation in order to improve model accuracy and robustness. 
• Tools/Technologies: Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, OpenCV, Keras, Jupyter Notebook

• Learned practical industry skills related to the field of Data Science particularly focusing on Computer Vision and Deep Learning, and applied them on a Custom Object Detection project

Moiz Sadiq Awan🇺🇸

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