Shariq Usoof
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Shariq
Usoof

Master of Data Science graduate with a Bachelor of Finance from Monash University. Built and deployed a full-stack application serving numerous users. Combining finance and data science allows me to bring technical capability and commercial understanding across various fields.

Currently working at the intersection of financial markets and data as a Trade Control Analyst at Fusion Markets.

Trade Control Analyst · Fusion Markets
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Technical Skills

Languages
Python R SQL JavaScript
Visualisation Tools
Power BI Tableau R Shiny Py Dash
Cloud Deployment & Databases
AWS Oracle Cloud Azure
Machine Learning Models
Machine Learning Deep Learning Graph Neural Networks
Financial Knowledge
Financial Modelling Portfolio Risk Analysis Volatility Modelling
AI Integration
OpenAI API Gemini API Copilot API
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My Work

Options Pricing & Analytics Platform
Personal Project
Jan 2026 – Present · Melbourne, AU
  • Built a live options analytics platform for pricing, screening, and contract analysis, deployed at options.shariqusoof.com.
  • Implemented American options valuation using a CRR binomial tree, with supporting sensitivity analysis for volatility and interest-rate changes.
  • Integrated live market and options-chain data through yfinance, with fallback handling for unavailable or incomplete ticker data.
  • Developed a Python Dash application with caching logic, reusable analytics functions, and a production deployment on Azure.
View details ↗
Financial Data Analyst
ERA Group (Chater Consulting Pty Ltd)
Aug 2025 – Mar 2026 · Melbourne, AU
  • Built an FX analytics application to compare client foreign exchange transaction rates against historical market benchmarks.
  • Automated the workflow for cleaning transaction data, retrieving market reference rates, calculating spreads, and generating reporting outputs.
  • Developed R Shiny dashboards and Power BI reports to help non-technical clients identify spread patterns and compare FX providers.
  • Deployed the solution using AWS EC2 and Amazon RDS to store client inputs, calculated spreads, and reporting outputs.
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Verilyx — Financial Fraud Detection
Cloak Solutions
Aug 2025 – Nov 2025 · Melbourne, AU
  • Built a fraud detection analytics pipeline for a cybersecurity client serving financial-services use cases.
  • Developed Kafka-based streaming workflows to process transaction and behavioural events for fraud monitoring and live reporting.
  • Created a Flask/React dashboard to visualise streaming risk signals, transaction patterns, and operational fraud metrics in near real time.
  • Added data validation and monitoring logic to support more reliable ingestion, scoring, and reporting for risk and audit users.
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ClassForge — Allocation System
SNA Toolbox
Mar 2025 – Jun 2025 · Melbourne, AU
  • Developed an AI-based classroom allocation system combining graph machine learning, social network analysis, and optimisation.
  • Used R-GCN/R-GAT models to generate student-level social and academic indicators, including influence, isolation, wellbeing, and GPA-related signals.
  • Implemented a multi-objective genetic algorithm to balance classroom allocations across academic performance, social cohesion, and wellbeing constraints.
  • Built an NLP layer that allowed teachers to express allocation preferences in natural language and convert them into adjustable optimisation constraints.
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UCF — Video Recognition
Machine Learning Challenge
May 2025 · Melbourne, AU
  • Built a video action recognition pipeline using selected classes from the UCF101 dataset.
  • Developed a CNN-LSTM deep learning model using ResNet-18 for spatial feature extraction and LSTM layers for temporal sequence modelling.
  • Preprocessed video data by extracting frames with Decord, resizing inputs, and applying ImageNet-based normalization for model training.
  • Compared deep learning performance with a traditional machine learning pipeline using handcrafted motion features and SVM classification.
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Multi-Cloud IPsec Tunnel Deployment
Personal Project
Mar 2025 · Melbourne, AU
  • Deployed a multi-cloud architecture using AWS and Oracle Cloud Infrastructure across separate virtual cloud networks.
  • Configured a site-to-site IPsec VPN tunnel to enable secure private communication between the two cloud environments.
  • Validated routing, security group rules, and cross-cloud traffic flow between deployed compute instances.
  • Researched private connectivity patterns and documented the trade-offs of VPN-based communication across cloud providers.
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Movie Review Sentiment Analysis
Personal Project
Feb 2025 · Melbourne, AU
  • Built a sentiment classification pipeline using Bag-of-Words and TF-IDF feature extraction on a movie review dataset.
  • Trained Multinomial Naive Bayes models using stop word removal, bigrams, and document-frequency thresholds.
  • Conducted cross-validation and hyperparameter tuning across multiple train-validation split configurations.
  • Evaluated model performance using precision, recall, F1-score, and prediction-level error analysis.
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US Socioeconomic Dashboard
Personal Project
Oct 2024 – Nov 2024 · Melbourne, AU
  • Designed Tableau dashboards analysing poverty, income, and education patterns across US states and counties.
  • Used socioeconomic datasets to compare demographic and geographic differences in poverty and median income.
  • Created visualisations focused on clarity, accessibility, and practical interpretation for non-technical audiences.
  • Produced written analysis explaining dashboard design choices, key trends, and regional socioeconomic disparities.
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Java Parking Terminal System
Personal Project
Sep 2024 – Oct 2024 · Melbourne, AU
  • Built a Java parking management system for creating, deleting, searching, and managing staff and visitor parking slots.
  • Structured the application using object-oriented classes for cars, parking slots, car park operations, and terminal interaction.
  • Extended the terminal-based system into a Swing GUI with slot interactivity, menu actions, and dialog-based validation.
  • Applied exception handling and OOP design principles to enforce parking rules such as duplicate cars, occupied slots, and invalid slot operations.
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