The Logician
About Me
I'm Hamza Khan, a product manager who builds trust infrastructure by breaking it first.
That isn't a tagline. It's literally how I work. Before I ship a product, I think about every way it could fail. Before I trust a system, I test it. Before I accept a claim, I verify it. It's the same instinct that led me to take a $2 nylon mask to AWS Rekognition's liveness API and publicly document the vulnerability, and the same instinct that drives me to build products that hold up under real-world scrutiny.
Career in Three Chapters
Chapter One: Breaking Things
At Facia, a biometric security company with a mature liveness detection product, my mandate as a Product Analyst was to think like a fraudster. I tested the system using 40+ generative AI tools, 3D masks, physical presentation attacks, and injection attacks.
I discovered that a $2 nylon stocking mask could spoof both Facia's system and AWS Rekognition, one of the most widely deployed facial recognition services in the world. I documented this publicly on LinkedIn. The adversarial dataset I built during this period directly enabled two new product lines: Deepfake Detection and AI Image Detection.
Chapter Two: Building from Zero
I moved from breaking products to building them. At Programmers Force, I took over AML Watcher when it had no product team. I built the function from zero, scaled the team from 2 to 10, and designed and shipped the core features the platform offers today.
The first thing I built end-to-end was adverse media screening, a context-aware, sentiment-analysed, multilingual monitoring system that I later spun off into its own product. That spin-off became Media Watcher, a zero-to-one media intelligence platform I conceived, named, and prototyped in two weeks. I also named and launched Barie.AI, an agentic AI platform that executes real work across business tools. Prototype in one month. 1,000+ waitlist sign-ups in two months.
Chapter Three: Scaling Impact
Now at Shufti, I own GTM across seven product lines, conceived and launched the Blind Spot Audit on AWS Marketplace, and prepare all Gartner and Liminal analyst briefings. This is product management when the metric is business outcome, not feature delivery.
How I Think
I'm an INTJ-A, sometimes called “The Architect” but better described, in my case, as a logician. I reason from first principles. I work backwards from the outcome. I'm uncomfortable with claims that haven't been tested and assumptions that haven't been stressed. When I encounter a trust system, my first question isn't “how does it work?” but “how does it break?”
This adversarial mindset doesn't make me a pessimist. It makes me a builder with higher standards. Every product I've shipped was made stronger because I found its weaknesses first. The $2 mask wasn't an attack on AWS. It was proof that the industry needed to do better.
Education & Certifications
BSc. Economics with Data Science
Information Technology University, Lahore · CGPA 3.51/4.0
The degree gave me a quantitative foundation in machine learning, econometrics, and statistical inference that informs how I think about product decisions, risk models, and data architecture.
Data Science Professional Certificate
Nine-course programme covering probability, inference, regression, and machine learning. Includes R programming, data wrangling with dplyr, visualisation with ggplot2, Unix/Linux, Git, and RStudio. Case studies in election forecasting, financial crisis analysis, and recommendation systems.
Verify Certificate
Business Analytics Specialization
Five-course Wharton programme covering customer analytics (descriptive, predictive, prescriptive), operations analytics, people analytics for recruiting and compensation, and accounting analytics linking financial and non-financial metrics to performance.
Verify Certificate
Google Advanced Data Analytics
Python, exploratory data analysis, data cleaning and visualisation with Tableau, descriptive and inferential statistics, hypothesis testing, linear and logistic regression, ANOVA, chi-square tests, and machine learning fundamentals using Jupyter Notebook.
Verify Certificate
Deep Learning Specialization
Five-course programme by Andrew Ng covering neural network foundations, CNNs, sequence models, and Python/TensorFlow implementation. Topics: Adam, Dropout, BatchNorm, Xavier/He initialisation, RNNs, LSTMs, with case studies in healthcare, autonomous driving, and music generation.
Verify CertificateTensorFlow Developer Professional Certificate
Four-course programme covering neural network construction in TensorFlow, computer vision with CNNs, image augmentation, NLP with RNNs/GRUs/LSTMs, text tokenisation, sequence modelling, and time series forecasting using deep neural networks.
Verify Certificate
Business Analytics Specialization
Data strategy, exploratory data analysis, and machine learning algorithms applied to business decision-making. Tools: Power BI, Alteryx, RStudio. Spans finance, marketing, retail, supply chain management, and social media analytics.
Verify CertificateML Engineering for Production (MLOps) Specialization
Full production ML lifecycle: project scoping, data pipelines, feature engineering with TFX, model serving, workflow automation, progressive delivery, model fairness, explainability, drift detection, and continuous retraining.
Verify Certificate
DevOps on AWS
Continuous integration, delivery, and deployment on AWS. Infrastructure as code with CloudFormation, automated release pipelines using CodePipeline, CodeCommit, CodeDeploy, and CodeBuild, IAM best practices, and operational monitoring.
Verify CertificatePractical Data Science on the AWS Cloud Specialization
Exploratory data analysis, AutoML, and text classification with SageMaker. End-to-end ML pipelines with BERT and Hugging Face, feature engineering with SageMaker Feature Store, hyperparameter tuning, A/B testing, and human-in-the-loop pipelines with Amazon Augmented AI.
Verify CertificateBeyond Work
I read seriously. Thrillers and psychological dramas are my genre of choice: the kind of book where every detail matters and careless readers miss the point entirely. On screen, my reference films are the ones that reward re-watching: The Godfather, Pulp Fiction, Fight Club, Blade Runner 2049, Inception. I approach anime the same way I approach product thinking, with attention to systems, consequences, and the rules characters operate by. Death Note, Attack on Titan, and Code Geass remain benchmarks for how to construct a narrative where intelligence is a competitive advantage.
I am a student of hip-hop. The way great rappers construct arguments through rhythm, layered meaning, and wordplay maps more closely to product strategy than most people would admit: both require making complex ideas land cleanly under constraints. Outside of that, I follow Football, Cricket, and Basketball, primarily because sport, at its best, is a clean system with clear feedback loops.