Hire the Best Quantitative Finance Freelancers
in the United Arab Emirates

🎖 Top Rated | 50+ clients | 10+ years building production backend & AI systems You've started building with AI — and the cracks are showing. Hallucinations you can't explain, agents that go off-script, a RAG pipeline that retrieves the wrong context half the time. A demo that impressed everyone and then fell apart on real data. That's exactly where I come in. I build LLM-powered systems that survive production: AI agents, RAG pipelines, and automation built on the data infrastructure they depend on. I work deep in the LangChain/LangGraph ecosystem with Anthropic (Claude API), OpenAI, and open-source models, shipping real products and internal tools for clients in fintech, GovTech, real estate, and edtech. Recent work: • Contract-bidding SaaS for US government procurement — AI agents monitor procurement portals, score opportunities against millions of records, and draft bid responses, cutting manual research time by 80% • Academic integrity platform using LLMs and ML to analyze writing patterns across 50,000+ monthly submissions • Real estate intelligence platform — 60+ concurrent scrapers feeding AI parsing and enrichment pipelines into a multi-region PostgreSQL system Where I spend most of my time: • Designing agent workflows with LangGraph, Make/n8n, and custom orchestration • Building RAG systems that are actually reliable — chunking strategy, retrieval tuning, eval pipelines • Wiring LLMs into FastAPI/Django backends with proper async handling, streaming, and error recovery • Deploying on AWS with Docker/Kubernetes, keeping costs predictable and latency sane at scale The difference: my foundation is 10+ years of backend engineering - Python, FastAPI, Django, PostgreSQL, SQLAlchemy, Celery, Redis, web scraping at scale. I don't just prompt-engineer. Most AI projects fail at the data layer, not the model - I build both. I'm selective about projects. I work best when there's a real problem to solve and a client who wants to understand what they're building, not just receive a black box. If that sounds like you, send me a message with a couple of lines about what you're building.

Quantitative Trading | AI/ML Systems | Low-Latency Execution | HFT Infrastructure I help systematic trading teams build production-grade quantitative trading systems that actually work in live markets. Over the past 10+ years, I’ve designed and deployed algorithmic trading infrastructure across FX, crypto, equities, and derivatives; covering the full pipeline from research and feature engineering to execution, monitoring, and risk management. My work focuses on solving one of the biggest problems in systematic trading: The gap between backtests and live performance. I specialize in: → Event-driven backtesting with strict point-in-time correctness → Low-latency execution systems & market microstructure → FX & crypto execution optimization → AI/ML signal research & feature engineering → Cross-venue and statistical arbitrage → Market making & inventory-aware execution → Risk-aware portfolio and position management → Tick-level & L2 order book data systems I build high-performance infrastructure using Python and C++, working with shared memory, mmap, multiprocessing, WebSockets, FIX APIs, REST APIs, Redis, and event-driven architectures. Selected work includes: → Point-in-time multi-asset backtesting engines → Low-latency market-making systems → Real-time FX & crypto arbitrage engines → Shared-memory tick processing pipelines → AI-driven signal research frameworks → Execution analytics & slippage analysis systems I focus on robustness over overfitting, execution over theory, and systems that behave realistically under live market conditions. If you're building or scaling a serious systematic trading operation and need help with research infrastructure, execution systems, backtesting, or production trading architecture, feel free to reach out. ------------ Notable Projects Built a high-performance event-driven backtesting engine designed around strict point-in-time correctness, capable of handling multi-asset data with realistic execution modeling. The system supports tick and bar data, corporate actions, and reproduces live trading behavior without lookahead bias, enabling reliable research-to-production transition. Designed and deployed a low-latency market making system based on inventory-aware pricing and microstructure signals. The system incorporates dynamic spread adjustment, adverse selection control, and execution optimization to maintain profitability under varying liquidity and volatility regimes. Developed a real-time cross-venue arbitrage engine across FX and crypto markets, integrating multiple brokers and exchanges. The system includes latency-aware signal validation, quote synchronization, execution throttling, and risk controls to capture short-lived inefficiencies in live markets. Engineered a shared-memory, ultra-low latency data pipeline between trading platforms and Python-based orchestrators using custom C++ DLLs and ring buffers. The system delivers sub-millisecond tick propagation with sequence tracking, enabling high-frequency strategies and real-time analytics. Created an entropy-based data mining framework for large-scale strategy discovery, focusing on information-theoretic feature selection to reduce overfitting and improve robustness. The framework evaluates thousands of indicators and permutations while controlling for data mining bias. Built advanced machine learning pipelines for alpha generation, including meta-labeling frameworks, probabilistic signal filtering, and feature engineering tailored to financial time series. Models are designed for stability across regime

I’m a Quantitative and Systematic Options Trader, Algorithmic Trading Specialist, and the Founder & CEO of Powertech Funds (India) and Powertech Global LLC (Dubai) — where we help hedge funds, asset managers, and sophisticated investors turn volatility into opportunity through tech-driven, data-backed trading strategies. My work has been featured on Moneycontrol, and I’ve also authored educational content on algorithmic options trading for Alpaca, a leading API-first brokerage platform. Over the years, I’ve built a reputation for designing high-alpha options strategies, risk-managed portfolios, and fully automated trading systems that perform across asset classes — from SPX 0DTE options and QQQ/SPY ETF strategies, to BTC and ETH derivatives, forex pairs like EUR/USD, and India’s Nifty and Bank Nifty futures. With more than 200 proprietary trading models across U.S., crypto, forex, and Indian markets, I combine deep market insight with advanced quant techniques and automation to deliver scalable, real-world performance. My guiding philosophy is simple: “Protect the base, invest the gains.” I advise a diverse client base — including crypto-native hedge funds, traditional family offices, high-net-worth individuals, and brokers — helping them build smarter, more resilient, and tech-forward trading operations. If you’re looking for someone who lives and breathes markets, understands both the math and the madness, and can help you scale alpha through intelligent automation — let’s connect.

We specialize in financial modeling and investor pitch decks that help startups and businesses make data-driven decisions and secure funding. Whether you need an investment-ready financial model or a compelling pitch deck, we deliver high-quality, structured outputs that align with investor expectations. Meet the Team: 👤 Dmitry Karavaev, CFA – Financial Expert | Investment & Valuation Specialist • 15+ years in finance, including managing a $600M portfolio at a Dubai-based family office and serving as Head of Research at a crypto fund. • Expert in financial modeling, valuation, investment strategy, and risk analysis. • Experience across private equity, structured products, derivatives, and crypto assets. • MSc in International Finance & CFA Charterholder. 👤 Alexei Rezvanov – Pitch Deck & Growth Marketing Specialist • Former Marketing & PR Manager at Graphene Ventures, a leading Silicon Valley VC firm focused on early stage investments. • Ex-owner of a digital production agency with a team of 25+ designers and developers who created web and mobile solutions for Hisense, Norilsk Nickel, Comepay, Louis Vuitton, Metso, Takeda and many others. • Created 50+ pitch decks that successfully helped startups attract investments. • Expert in business modeling, financial storytelling, and investor-ready presentations. • Strong background in market research, digital ventures, and startup strategy. What We Offer: ✅ We apply various valuation methodologies, including DCF, precedent transactions, comparable company analysis, LBO modeling, and asset-based valuation. ✅ Pitch Decks & Investor Presentations – Engaging, data-driven decks that tell a compelling story. ✅ Video Pitch Deck – Your pitch, packed in 25-40 sec video with professional voiceover. ✅ Market Research & Competitive Analysis – Insights to strengthen financial projections. ✅ Fast Turnaround & High Accuracy – Delivering high-quality results within 48 hours. 📩 Let’s craft investor-ready financial models and pitch decks to help your business secure funding!

Skills Summary: Proficient in Python, R, SQL, and LaTeX. Expert in machine learning, deep learning, and natural language processing, with extensive experience in clustering, data visualization, and econometrics. Skilled in statistical and time series analysis, proficient with version control systems, web scraping, and big data technologies. Background: - Bachelor's in Mathematics and Statistics from Newcastle University, UK - Advanced studies in Data Science at the University of Warsaw, Poland. Experience: - Currently a Data Scientist-Algo Trader Model Developer at a fintech startup, enhancing trading strategies and developing a flexible backtesting framework. Innovations include optimizing Moving Average parameters across S&P 500 sectors, refining the Squeeze Pro Strategy for improved returns and signal accuracy, and crafting a Generalized Backtesting Framework to customize strategy optimizations based on specific performance metrics. - Over three years at Citibank, advancing from an intern to Assistant Vice President in Algo Trading. Led over 20 cross-assets model validation projects, including rigorous testing and implementation of alternative models.