How I Work
I like problems where getting the logic right is the hard part.
That can mean isolating a connectivity failure, walking someone through recursion, or reasoning about memory, threads, and file systems until the behavior makes sense.
Satyam Bhanot · Computer Science Honours
Backend developer and data/ML builder.
CS Honours graduate from the University of Manitoba with a Math and Statistics minor. I build backend systems, data pipelines, and ML experiments — and debug them until they hold up.
6 Projects
systems, backend, data, ML
Java · Python · C
primary languages
3.90 GPA
Dean's Honour List, Fall 2024
Personalized Snapshot
The through-line is understanding how systems actually behave.
Systems
C, Linux, OS concepts, debugging tools.
I like projects where the machine's behavior is visible and precision matters.
Support
50+ incidents handled weekly.
Support taught me to stay calm, document clearly, and solve problems under real user pressure.
Teaching
One-on-one tutoring and mentorship.
Good technical communication starts by finding the exact point where someone got lost.
Selected Work
Six projects across backend, data, ML, and systems.
Machine Learning
Credit Card Fraud Detection
Compared 6 classifiers — Logistic Regression, Decision Tree, Random Forest, KNN, XGBoost, and LightGBM — for fraud detection on a highly imbalanced dataset. Used SMOTE and class weighting to handle class imbalance.
What stuck with me: how much the choice of evaluation metric matters when positive cases are less than 0.2% of your data.
Pythonscikit-learnXGBoostLightGBMSMOTE
Computer Vision
Where's Waldo? CNN Detection
Compared YOLOv8, RetinaNet, SSD MobileNetV2, and a custom CNN for Waldo detection across annotated and synthetic image data. YOLOv8 achieved the best F1 score; RetinaNet delivered the highest precision.
What stuck with me: the gap between precision and recall tells you something real about how each architecture reasons about ambiguous cases.
PythonPyTorchYOLOv8RetinaNetSSD
COMP 4360 · Machine Learning · University of Manitoba
Data Engineering
Winnipeg City Analysis
Analyzed best Winnipeg neighbourhoods using multi-source civic data — transit stops, parks, hospitals, and 911 incidents — fetched via the City of Winnipeg open data API and joined across inconsistent schemas.
What stuck with me: joining across data sources forces you to make explicit decisions about what "same location" actually means.
JavaSQLREST API
COMP 3380 · Databases · University of Manitoba
Systems Programming
ExFAT Shell
Built a custom shell in C for interacting with an ExFAT file system, including UNIX-style commands, process execution, I/O redirection, and piping.
What stuck with me: reliable tools feel simple only after the parsing, errors, and edge cases are handled carefully.
CLinuxFile SystemsProcesses
COMP 3430 · Operating Systems · University of Manitoba
Concurrency
Cooperative Threads Library
Implemented a C thread library modeled on pthread-style behavior, with mutex support and FIFO, round-robin, and MLFQ scheduling policies.
What stuck with me: concurrency becomes easier to reason about when scheduling and synchronization rules are explicit.
CSchedulingMutexesValgrind
COMP 3430 · Operating Systems · University of Manitoba
Software Engineering
PetObject
Built an Android app with a team for managing a virtual pet, with a focus on validation, navigation, editing flows, testing, and maintainable project structure.
What stuck with me: collaboration gets much easier when architecture and tests make the app predictable.
JavaAndroidHSQLDBJUnit
COMP 3350 · Software Engineering 1 · University of Manitoba
More on GitHub →
Experience
Technical work, support, and mentorship.
May 2023 to Present
Tech Support Specialist
Rogers Communications · Remote
I troubleshoot hardware, software, and network issues while keeping documentation clear enough for future support and escalation work.
- Resolve 50+ incidents and service requests weekly.
- Document issue patterns, asset records, escalations, and service outcomes.
- Coordinate with network engineering and field operations on complex issues.
Sep 2023 to Aug 2025
Peer Tutor
UofM Science Students' Association · Nimbus Learning
I helped students work through computer science, mathematics, and statistics by slowing concepts down and rebuilding confidence from first principles.
- Delivered one-on-one and group sessions in CS, mathematics, and statistics.
- Built practice problem sets and step-by-step explanations for common sticking points.
- Helped students move from memorization to independent problem solving.
2024 to Present
Student Mentor and Campus Leader
University of Manitoba
I support incoming and international students through orientation, mentorship, resource navigation, and student community work.
- Mentored incoming and international Science students through academic and social transitions.
- Supported international students in navigating university systems and campus resources.
- Served as Treasurer for the Statistics Club — managed budget and financial reporting.
Education
Computer Science Honours with a Math and Statistics minor.
Bachelor of Science · University of Manitoba · Graduated April 2026
Dean's Honour List · Fall 2024, GPA 3.90
University 1 Honour List · Winter 2021, GPA 3.83
Operating Systems
Databases
Machine Learning
Security
Algorithms
Statistics
Skills
Grouped by how I use them.
Backend & Apps
APIs, services, and application logic
JavaPythonJavaScript
Node.jsFastAPIReact
Systems & Low-level
C-level programming, debugging, memory
CC++Linux
gdblldbValgrindMakefile
Data & ML
Pipelines, analysis, and model work
SQLPostgreSQLMongoDB
RJupyterscikit-learn
Workflow & Tools
Dev process and collaboration
GitDockerGitHub
Figmatestingdocumentation
Contact
Open to backend SWE, data engineering, and ML engineering roles.
New grad, available now. If something here connects with the work you need done, send me a note.
satyambhanot@gmail.com