I am a software engineer and machine learning practitioner with
hands-on experience building production-grade fraud detection and
AML compliance systems for fintech clients in the UK.
My work spans end-to-end: from raw transaction data to deployed
rule engines, anomaly detection models, and interactive compliance
dashboards.
WHAT I BUILD FOR YOU:
- AML/KYC Systems: rule engines, customer risk scoring, anomaly
detection (Isolation Forest, Mahalanobis Distance, DBSCAN)
- ML Pipelines: clustering, classification, dimensionality
reduction (t-SNE, diffusion maps, PCA)
- Python Backend: data processing, REST API integration,
ETL pipelines, automated reporting
- JavaScript / Vue.js Frontend: compliance portals, dashboards,
data visualization
- Data Analysis & Reporting: customer segmentation, risk
profiling, structured Word/Excel report generation
WHY WORK WITH ME:
- IIT Roorkee engineering graduate, strong mathematical and
algorithmic foundation
- Currently building AML fraud detection systems for a
London-based fintech firm
- Clean, well-documented code with proper test coverage
- Reliable delivery, clear communication, timezone-flexible
Whether you need a fraud detection prototype, a compliance
dashboard, a custom ML pipeline, or a data-driven web
application, I deliver production-quality work with precision.
Let's discuss your project.