Engineering decision support frameworks for complex regulatory data.
Seasoned Data Science Professional with 7 years of experience in delivering analytical solutions and decision support across diverse business sectors. Currently working as a Specialist Data Scientist within a federal regulatory body in the UAE.
A track record grounded in production systems
Seven years translating statistical rigor into deployed decision support, across regulatory, corporate, and digital domains.
A career built on enterprise data architecture
Delivering advanced machine learning, forecasting, and AI systems.
Specialist Data Scientist — Fraud Prevention & Supervision
Design, deploy, and evaluate surveillance algorithms and supervision frameworks for domestic entities. Focus areas include:
- High-throughput transaction anomaly classification and network flow modeling.
- Advising on risk frameworks and data governance models across domestic banking systems.
- Supervising machine learning risk parameters and validating compliance scorecards.
Senior Consultant, Engineering AI & Data
Delivered advanced AI solutions and digital transformation roadmaps for government and corporate clients:
- Implemented a Gen AI, RAG-based chat application for a government entity leveraging Dubai's open datasets, enabling natural language queries with responses generated through LlamaIndex Text-to-SQL.
- Led the implementation of MLOps, compared the client's setup with industry best practices, and developed plans to improve their machine learning deployment.
- Designed and implemented cardholder personas through analysis of transaction data for customers across Saudi Arabia (KSA), driving enhancements in customer experience and service personalization.
- Carried out an employee turnover study with limited data, discovering important insights using Dataiku that helped shape the client's data science strategy.
- Assisted in the upgrade of NEOM's marketing systems, identifying key areas for improvement and planning strategic upgrades.
- Contributed to AI strategy development for government and private sector clients, defining AI governance frameworks and identifying high-impact AI use cases.
Senior Data Scientist
Led consumer analytics and marketing forecasting engagements:
- Improved leads conversion rate by 30% by developing a propensity model on clickstream data that learns to differentiate between high and low propensity users visiting the website based on their behavior.
- Built 10+ forecasting models to track 6 website KPIs and a system that notifies relevant stakeholders of any significant changes in KPI values depending on set business rules.
- Implemented leads forecasting models that led to over a 20% increase in meeting leads acquisition goals.
Technology Consultant
Engineered predictive planning systems and proofs of concept:
- Developed a demand forecasting solution identifying an opportunity to increase the market share of a logistics company by 15% by building Monte Carlo simulations that simulate the flow of product throughout the country.
- Built a PoC showcasing capabilities of voice analytics and its application in call center management.
Independent builds and technical deep-dives
Work outside the day job — agentic systems, architecture experiments, and the occasional deep-dive into a paper worth implementing.
Agent-DASC Architecture
Agent-DASC is modeled directly on Google's DS-STAR agentic framework. It automates multi-step, heterogeneous data science tasks by coordinating eight specialized agents (Analyzer, Planner, Coder, Executor, Debugger, Router, Verifier, and Finalizer) through a LangGraph state machine — planning, executing in a sandboxed container, and iterating until a verifier judges the result sound.
Technical documentation, case studies, and engineering briefs
Reflections on building analytics agents, risk architectures, and data frameworks.
First Principles: What Is Legal Tender, and What Is a CBDC?
Before the design questions and the policy debate: what legal tender actually means, and what a central bank digital currency actually is, according to the institutions building them — sourced from the Fed, the Bank of England, the BIS, the IMF, and the ECB.
What colleagues have said
A few words from managers, clients, and teammates across my career.
I have known Azhar for more than 6 years. In fact we have recruited him into DXC Technology after a tough entrance test and a rigorous interview process with hundreds in the competition. He has good knowledge of Data Science fundamentals and he is excellent in hands-on Python programming. He is always learning new things in data science. Azhar brings in the qualities of focus-on-work and team-spirit. We had great fun and success in multiple international trips and projects.
Azharuddin Kazi is a dedicated, focused and objective professional. He worked on a complex project as a data scientist and made the deliveries as agreed.
I had the pleasure to work with Azhar on a very challenging project for an agribusiness firm in Brazil. Azhar demonstrated a lot of technical and interpersonal skills — his work was oriented toward building a complex predictive model, which was deemed very good by the client. He stayed in Brazil for a long period, which brought him a lot of good multicultural experience. I definitely recommend him.
Let's connect
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