About Me
AI & Data Professional with 5+ years of experience working on projects related to Machine Learning, Data Mining, Cloud Computing & Software Engineering.
Most recently I was working as a Technical Consulant at N. Harris Computer Corporation.
My background is in data mining and machine learning with applied research experience working at the Data Mining Lab, York University. Previously, I’ve worked as an MLOps Engineer at a Google Cloud Platform (GCP) consulting company where I leveraged GCP ML stack to deliver end-to-end machine learning models. I also did certification in GCP as a Professional Machine Learning Engineer.
I have experience working with Geo-Spatial Data sets for which I used PostgreSQL & PostGIS and Python to extract insights. I typically visualize data sets along the way to understand the pipelines and models I’m creating.
I conducted research as an Erasmus Scholar @ the Department of Information Technology, Uppsala University, Sweden in the area of Cloud Computing.
During my graduate studies at York University, I was working under the supervision of Prof. Manos Papagelis.
Interests: data mining, machine learning, data science, natural language processing (NLP), cloud computing
Technical Knowledge and Skills:
• Data Mining & Visualization - Python (matplotlib, seaborn, pandas, numpy), PySpark, Power BI/Tableau
• Programming Languages - Python, Java, C#, C/C++
• Databases - PostgreSQL/PostGIS, MongoDB, MySQL
• Google Cloud Platform (GCP) - Vertex AI, BigQuery, Dataflow
• NLP & Machine Learning - spaCY, NLTK, Tensorflow/PyTorch/Keras
• Operating Systems - Linux/Mac, Windows
Experience
N. Harris Computer Corporation
Technical Consultant/Software Engineer
Apr 2023 - Mar 2025
• Designed Data Pipelines to extract, transform and load (ETL) data from customer information systems (CIS) into meter data management (MDM) software
• Managed the processing, transformation and extraction of meter data coming from advanced metering infrastructure (AMI) systems
• Implemented modules such as line loss analysis, leak detection and transformer load analysis
• Collaborated with clients to understand their requirements and implementing customized solutions based on their needs
• Contributed towards the implementation of in-house large language model (LLM) based module
Badal.io
MLOps Engineer
Apr 2022 - Jan 2023
• Built end-to-end machine learning models (training, deployment & evaluation) using AutoML and custom model training by leveraging Vertex AI, BigQuery, Docker and Dataflow for a client in financial space. Improving their ability to train ML models more efficiently using GCP
• Developed proof-of-concepts to detect bias in appraisal documents, leveraging Document AI and Cohere API
• Certified Google Cloud Professional Machine Learning Engineer
Certificate URL: https://bit.ly/3WhLBzg
EECS, Lassonde School of Engineering, York University
Graduate Teaching Assistant
Jan 2018 - Dec 2022
Taught multiple courses at the Electrical Engineering and Computer Science (EECS) department
• Courses: Programming for Mobile Computing EECS 1022 - Introduction to Database Systems EECS 3412 - Object Oriented Programming from Sensors to Actuators - EECS 1021 - Software Design - EECS 3311
Tasks include: directing tutorials, exam invigilation, final and midterm exam review sessions, grading assignments/exams, office hour duties. OOP, Java, Android Studio, IntelliJ
Data Mining Lab, Lassonde School of Engineering, York University
http://dminer.eecs.yorku.ca/Graduate Research Assistant
Jan 2018 - Apr 2020
• The research was related to trajectory data mining, machine learning, and statistical inference
• Developed a method that utilizes trajectories of [cars, pedestrians, etc.] as a way to infer semantic similarities between geographical areas
• Published the research titled Learning Semantic Relationships of Geographical Areas based on Trajectories at the IEEE Mobile Data Management Conference 2020 Versailles, France, and received Best Paper Award
Swedish National Infrastructure for Computing, Uppsala University
Erasmus Scholar
Aug 2015 - Jan 2016
• Designed a framework inside SNIC using Apache Spark, SparkR & Jupyter Notebook to simplify computations of highly parallel scientific applications
• Our project titled Towards Moving Scientific Applications in the Cloud enabled researchers to seamlessly deploy their applications on the spark server and scale it to multiple worker nodes as needed
Notable Projects
Learning Semantic Relationships of Geographical Areas based on Trajectories
https://github.com/saimmehmood/semantic_relationshipsPython (networkx, pandas, numpy, seaborn, matplotlib), PostgreSQL, PostGIS, MATLAB, Google Cloud (Places & Directions) API
• Developed a framework to understand semantic relationships between geographical areas based on object movement paths i.e., trajectories. (Best Paper Award for IEEE Conference on Mobile Data Management 2020)
Expert Developer Recommendation Using Very Large Datasets
https://github.com/saimmehmood/ExpertDeveloperRecommendationSQL, Google BigQuery, Elasticsearch
• Built a search engine to find expert developers by utilizing GitHub datasets. • Reduced 3TB of data into merely 600 MB by keeping developer specific information such as (number of commits, first and last commit, average time between commits etc.)
Towards Moving Scientific Applications in the Cloud
https://github.com/saimmehmood/Towards-Moving-Scientific-Applications-in-the-CloudCloud Computing, OpenStack, Apache Spark, Jupyter Notebook
• Cloud computing provides usability, scalability and on demand availability of computational and storage resources, remotely. These are the characteristics required by scientific applications and that’s why we used it. The project had two dimensions. First one addresses the benefits of cloud infrastructure for end users. In the second portion, we tried to do performance analysis.
COVID-19 - Risk of Geographical Areas being infected
https://towardsdatascience.com/covid-19-risk-of-geographical-areas-being-infected-a81938a5e286PostgreSQL, PostGIS, Python (numpy, pandas)
• This experimental project was done as a use-case to predict COVID-19 infection hotspots for a probable second wave of cases in Manhattan area.
Education
York University
MSc Computer Science
Jan 2018 - June 2020
York University is a public research university in Toronto, Ontario, Canada. It is Canada's third-largest university, and it has approximately 55,700 students, 7000 faculty and staff, and over 315,000 alumni worldwide.
My studies at York University were focused on extensive research. I accumulated a wealth of knowledge in the area of Data Mining, Big Data, Data Science and Machine Learning. I published research track paper with my supervisor Manos Papagelis, titled Learning Semantic Relationships of Geographical Areas Based on Trajectories for The 21st IEEE International Conference on Mobile Data Management 2020. Our paper received Best Paper Award.
Notable Courses: Data Mining, Mining Software Engineering Data
University of the Punjab
Bachelor of Sciences in Software Engineering
Sep 2012 - Jul 2016
University of the Punjab is a public research university located in Lahore, Punjab, Pakistan. It is the oldest public university in Pakistan.
Four years of undergrad at University of the Punjab helped shaped my understanding of cloud computing, software development, and its requirements engineering. During the course of my studies, I earned an Erasmus Mundus scholarship to spend an exchange semester at Uppsala University.
Notable Courses: Applied Cloud Computing, Software Requirements Engineering, Database Systems
Certifications
Google Cloud Certified Professional Machine Learning Engineer
https://www.credential.net/42cc4d30-75be-410c-8486-a94afbe73effIntroduction to Quantum Computing
http://www.linkedin.com/learning/introduction-to-quantum-computingCertificate No: AY7IBy3zoehD_C4j4fc-gqdE_brr
Volunteer Experience
• Helping recent graduates and folks from different backgrounds to transition into Data Science.
• Mentor Profile: https://app.sharpestminds.com/mentor-bio/saim-mehmood
• Open sourcing NLP (natural language processing) packages to increase the visibility of aggregate intellect in tech community - https://tinyurl.com/hz7bhrch
COVID-19 - Risk of Geographical Areas being infected - Python, PostgreSQL - PostGIS
• Using my existing research in trajectory data mining, developed a method to identify areas that are at a high risk of being infected by COVID-19 in the NYC Manhattan region.
Calculating Zakat using Python - Python, PyPDF2
• Utilized PyPDF2 to parse bank statements and generate the analysis and calculation.
• Actively contributed to organizing IBM’s CASCON x EVOKE 2019 conference.
Honors and Awards
Alongside my interests in data mining and software engineering I earned some awards:
- Awarded York University Graduate Fellowship for the entire duration of M.Sc. Computer Science, January 2018
- Electrical Engineering and Computer Science Graduate Student Association (EECS-GSA) York University, Vice-President Organization, Sep 2018 - 2019
- Represented Pakistani youth in China, Pakistan Youth Delegation, August 2016
- Won Erasmus Mundus Exchange Scholarship to spend an exchange semester at Uppsala University, May 2015
- Winner 17th In-House Speed Programming Competition, University of the Punjab, May 2015