Arslan Arslan

Hafiz Muhammad Arslan is a seasoned Data Scientist with over four years of extensive industry experience, specializing in the eCommerce, fintech, and healthcare sectors. His professional journey includes significant contributions to US-based startups and companies such as Neolytica.AI and CUNA Mutual Bank. At Neolytica, he played a pivotal role in developing and enhancing Big Data pipelines, which processed massive healthcare datasets to generate valuable insights for pharmaceutical clients. His expertise spans time series forecasting and machine learning (ML) solutions within the fintech domain, proficiently utilizing Python and its associated ML libraries including Pandas, Numpy, Scikit-Learn, Plotly, TensorFlow, Spark, and AWS.

Sr. Data Science Developer

Neolytica - A QPharma Company

Duration: July 2022 - Present (1 year 9 months)

Arslan has been instrumental as a Senior Data Science Developer at QPharma, Inc. His work involved tackling complex big data analytics projects. He developed innovative features and delivered analytical reports to pharmaceutical clients, enabling them to identify community leaders and key opinion leaders in specific medical fields. This strategic insight significantly bolstered the clients' sales campaigns for both new and existing drug brands.

Teaching Assistant

Information Technology University

Duration: March 2022 - August 2022 (6 months)

Arslan served as a Teaching Assistant, imparting knowledge and supporting the academic growth of students in the field of Information Technology.

Data Scientist

CUNA Mutual Group

Duration: September 2019 - June 2022 (2 years 10 months)

At CUNA Mutual, Arslan developed financial forecasting models to predict potential credit union defaults within two years post-COVID-19, utilizing 15 years of historical data. Additionally, he crafted a machine learning model to classify top-performing insurance advisors based on their sales performance over the last four quarters. He collaborated with DevOps teams to deploy these models on Microsoft Azure.

Research Assistant

Intelligent Machine Lab

Duration: June 2021 - September 2021 (4 months)

Contributed to solving 3D reconstruction problems using NeRF technology.

Research Intern

Motive

Duration: January 2019 - January 2020 (1 year 1 month)

Arslan developed a real-time off-roading detection system leveraging motion data. He engineered a data collection module incorporating IoT sensors like IMU, GPS, and OBD, coupled with a camera, configured with ROS, and collected data across various terrains. After analyzing and cleaning the data, he employed models like SVM, ANN, and Random Forest to differentiate between off-road and smooth-road conditions, ultimately finalizing a Linear SVM model.

Teacher Assistant for Artificial Intelligence Course

National University of Computer and Emerging Sciences

Duration: August 2019 - December 2019 (5 months)

Assisted in teaching an Artificial Intelligence course under Professor Dr. Kashif Zafar, Ph.D.

Web Developer

Qbatch

Duration: June 2017 - November 2017 (6 months)

Worked as an ROR Developer, contributing to web development projects.

Master of Science - MS, Data Science

Information Technology University

Years: 2020 - 2022

Bachelor of Science - BS, Computer Science

National University of Computer and Emerging Sciences

Years: 2014 - 2019

Full Stack Development Certification, Computer Software Engineering

Free Code Camp

Year: 2016

• Intro to Python for Data Science - DataCamp
• Neural Network and Deep Learning - Coursera
• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning - Coursera

• Deep Learning
• Big Data
• Apache Spark
• Pandas (Software)
• Machine Learning
• Amazon Web Services (AWS)
• Python (Programming Language)
• Data Analysis
• Data Science
• Scikit-Learn