Hafiz Muhammad Arslan
Lahore
--
linkedin.com/in/hfzarslan
Summary
I am a Data Scientist with 4+ years of industry experience working with US-based startups and companies in
the eCommerce, fintech, and healthcare domains, such as Neolytica.AI and CUNA Mutual Bank. During my
time at Neolytica, I worked on building and expanding the company's Big Data pipelines that ingested very large
volumes of healthcare data and provided key insights to pharmaceutical clients. Besides this, I have solid handson experience working on time series forecasting and ML problems in the fintech domain, and I have hands-on
experience with Python and its relevant ML libraries, like Pandas, Numpy, Scikit-Learn, Plotly, Tensorflow, Spark,
and AWS.
Experience
Sr. Data Science Developer
Neolytica - A QPharma Company
Jul 2022 - Present (1 year 9 months)
As a Senior Data Science Developer, I worked on some interesting big data analytics use-cases at
QPharma, Inc. I have developed new features and presented analysis reports to our Pharma clients that
helped identify community leaders and key opinion leaders in specific areas of medicine. This analysis
helped the company's Pharma clients in their sales campaigns for new and existing drug brands.
Teaching Assistant
Information Technology University
Mar 2022 - Aug 2022 (6 months)
Data Scientist
CUNA Mutual Group
Sep 2019 - Jun 2022 (2 years 10 months)
As a Data Scientist working for CUNA Mutual, I was responsible for building financial forecast models to
predict which credit unions under CUNA's purview would default in 2 years after COVID-19 hit based on
15 years of historical data. I was also responsible for building an ML model to classify top angels (topperforming insurance advisors) based on insurance products sold in the last 4 quarters. I worked with
the company's DevOps resources to deploy these models on Microsoft Azure.
Research Assistant
Intelligent Machine Lab
Jun 2021 - Sep 2021 (4 months)
Worked on 3d reconstruction problems, Nerf
Research Intern
Motive
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Jan 2019 - Jan 2020 (1 year 1 month)
• Built a real-time off-roading detection system using motion data.
• Created a small data collection module which had IOT based sensors including IMU, GPS, Camera,
OBD and configured with ROS and collected data on Ring road, Motorway and DHA roads. IMU was
used to capture linear acceleration and angular velocity in 3D, GPS unit, OBD-II for vehicle data and
USB cam for ground truth.
• Analyzed the sample data first for the feasibility of problem and then cleaned all captured data, found
out which features were important or redundant and was there any bias in data. For this problem we
engineered the statistical and frequency based features.
• We tested out multiple models like SVM, ANN and Random Forest on different distributions of data to
differentiate between off-road and smooth-road.
• Finalized a Linear SVM model trained on augmented IMU data with mean and standard deviation as
features after multiple experiments.
Teacher Assistant for Artificial Intelligence Course
National University of Computer and Emerging Sciences
Aug 2019 - Dec 2019 (5 months)
Teacher Assistant for Artificial Intelligence course under “Professor Dr. Kashif Zafar” - Ph.D (Computer
Science).
Web Developer
Qbatch
Jun 2017 - Nov 2017 (6 months)
ROR Developer
Education
Information Technology University
Master of Science - MS, Data Science
2020 - 2022
National University of Computer and Emerging Sciences
graduation, BS Computer Science
2014 - 2019
Free Code Camp
Full Stack Development Certification, Computer Software Engineering
2016 - 2016
Licenses & Certifications
Intro to Python for Data Science - DataCamp
2,722,518
Neural Network and Deep Learning - Coursera Course Certificates
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JXMZW9KP3SWQ
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and
Deep Learning - Coursera Course Certificates
KN6TC4U2KFPM
Skills
Deep Learning • Big Data • Apache Spark • Pandas (Software) • Machine Learning • Amazon Web
Services (AWS) • Python (Programming Language) • Data Analysis • Data Science • Scikit-Learn
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