Hi, I'm Faraz Jawed
ML/AI Engineer and Data Scientist
Currently a AI and Data Consultant at The World Bank
I transform complex data into actionable insights and build intelligent systems that drive business growth. Duke University graduate with a Master's in Data Science, specializing in AI safety research and quantitative finance applications. Currently developing AI-powered solutions for global development initiatives.

About Me
With expertise spanning quantitative finance, machine learning, and generative AI, I bridge the gap between cutting-edge technology and real-world business solutions. My work has generated millions in revenue, improved trading algorithms by 10%, and enhanced user experiences for thousands of customers.
From developing AI safety frameworks for Meta's Llama models to creating profitable trading strategies at Barclays, I thrive on solving complex problems with innovative data-driven approaches.
My Journey
From Finance to AI Innovation
Started my career combining finance expertise with programming skills, quickly discovering the power of data science to solve real business challenges. Over the past few years, I've evolved from analyzing market trends to building sophisticated ML models that predict user behavior, optimize trading strategies, and ensure AI safety.
My passion lies in creating intelligent systems that don't just process data, but generate meaningful insights that drive strategic decisions. Whether it's identifying high-value customer segments or developing low-latency trading algorithms, I focus on solutions that deliver measurable impact.
Recently completed my Master's in Data Science at Duke University, where I specialized in natural language processing, deep learning, and statistical modeling while contributing to cutting-edge AI safety research.
Skills & Technologies
Data Science & ML
Engineering & Cloud
Financial Technology
Visualization & Reporting
Automation
Work Experience
Building impactful solutions across AI safety, quantitative finance, and product growth
- •Engineered LLM-powered autonomous agents leveraging OpenAI and Azure APIs to reconcile global fixed income and derivatives trades, cutting reconciliation errors and manual time by over 40%
- •Automated portfolio risk reporting for $300b+ AUM by designing Python workflows that extract, aggregate, and validate multi-currency exposures across asset classes in minutes, not hours
- •Developing AI-powered solutions for global development initiatives and policy analysis
- •Collaborating with international teams on data-driven development projects
- •Co-authored IEEE Access paper establishing industry benchmarks for text-to-image (T2I) model safety datasets
- •Evaluated and strengthened Meta's T2I model safeguards by developing adversarial prompts and policy-guided test cases, directly improving defenses against political misinformation and harmful content ahead of the 2024 US Election
- •Built and launched a platform for collecting and annotating culturally sensitive prompts from 10 global geocultures, supporting the creation of an open-source benchmark dataset to improve cultural safety in GenAI systems
- •Rotated across Flow volatility derivatives Trading (equities), Electronic FX trading and Systematic Credit Trading
- •Developed clustering algorithm to classify incoming client RFQs into 4 tiers, improving algo hit-rate and quote-rate by 10%
- •Analyzed carry trades based on FX client flow to predict exit timing from hedge-fund clients, improving average hedging cost
- •Created low-latency interactive dashboard monitoring market flows and notifying team of possible exit trades
- •Built bi-directional strategy for RTY (Russell 2000 index) using technical indicators and Bloomberg API, achieving 65% accuracy in predicting next minute log returns
- •Boosted conversions by 12% in 6 months using XGBoost to pinpoint high-value user segments through engagement features
- •Identified key customer trends using SQL (PostgreSQL and AWS Redshift), improving KPIs (AUM, Net Deposits, Cumulative Funded Accounts) by 35% in 8 months
- •Developed CRM and marketing frameworks, achieving 33% CPI decrease and 14% MoM increase in daily app users
- •Pioneered comprehensive pricing model implementation, enabling $0.98 per trade fees and generating company's inaugural revenue stream
Featured Projects
A selection of projects showcasing full-stack development, AI/ML, and research capabilities

Key Highlights:
- •Natural language to 3D visualization conversion
- •Immersive XR data exploration on Meta Quest
- •Spatial LLM embedding visualization
- •24-hour hackathon development

Key Highlights:
- •IEEE Access publication
- •Industry benchmarks for T2I safety
- •10 global geocultures analysis
- •Open-source safety dataset

Key Highlights:
- •Multimodal learning with shared embedding space
- •External knowledge integration via DBPedia
- •Contrastive learning optimization
- •Real-world applications in education & healthcare

Key Highlights:
- •<1s delay with FAISS vectorized database
- •Real-time sports data integration
- •Hackathon winner
- •Multimodal AI implementation
Latest from My Blog
Sharing insights on AI, data science, and quantitative finance