Hire the Best Regex Specialists in London, UK

👋 Hi! I’m a Web Scraping specialist with strong experience in Python, BeautifulSoup, Selenium, Scrapy, and API extraction. I help businesses collect, clean, and structure data from websites—quickly and accurately. I can help you with: ✅ Web Scraping from any website (static or dynamic) ✅ Building custom scraping bots ✅ Automation for repetitive browser tasks ✅ Data extraction from e-commerce, directories, real estate, social sites ✅ Scraping protected/JavaScript-heavy sites using Selenium or Playwright ✅ API integration & reverse engineering ✅ Data cleaning & formatting (CSV, Excel, JSON) ✅ Bypass anti-bot systems (Cloudflare, captchas – ethically only) Tools & Technologies: Python, BeautifulSoup, Requests, Selenium, Scrapy Playwright, Puppeteer (JS) Pandas, Regex, XPath Postman, API testing Proxies & rotating user-agents MySQL, MongoDB, Excel automation Why Work With Me? ⭐ Fast delivery ⭐ Clean, maintainable code ⭐ Free sample or trial task ⭐ 100% accuracy ⭐ Clear communication & progress updates I’m here to save you time by automating the boring stuff. Let’s discuss your project and get your data in the format you need!

Most AI projects fail at the data layer, not the model. I build LLM systems that run on real production data: web scraping, data extraction, RAG, AI agents, and the evals that prove the output is right. Anyone can call an LLM API now. The hard part is getting reliable data in, and knowing whether what comes out is actually correct. Recent work - A scheduled collection and classification pipeline that has run unattended in production for six months. It pulls tens of thousands of records a day from a large marketplace via API and scraping, into a structured database, filters 65% of them out deterministically before any LLM spend, then classifies and scores the rest against comparable market data. Qualifying results publish straight into a spreadsheet the client works from, so buying decisions get made on scored data rather than manual research. - Claude wired into a client's internal systems: CRM, WhatsApp and email, with agents working alongside the team in a shared channel. I scoped the permissions and connector architecture end to end. Ongoing, with more of their processes automated as we go. - A multi-agent financial modelling pipeline for a real-estate underwriting platform. Document extraction, agent orchestration with LangGraph and FastAPI, and formula-driven Excel output for scenario analysis. Taking what took analysts days or weeks to do down to minutes. What I build - Data extraction at scale. Playwright, Selenium, PyDoll, BeautifulSoup, high-concurrency async, proxy infrastructure. Pipelines with retries, checkpointing, validation and structured logging that keep running when sites change or fail. - LLM systems in production. RAG, structured extraction, agent orchestration with LangChain and LangGraph, MCP servers and Claude Connectors wiring models into the tools a business already uses. Claude, OpenAI, Gemini and open models, used programmatically. - Evaluation and reliability. Golden sets, LLM-as-judge validated against human labels, regression tests in CI. Most teams ship AI features without knowing whether quality has dropped. I build the measurement systems. - Infrastructure. Python, FastAPI, Postgres and pgvector, Docker, GCP and Azure, scheduled cloud jobs with proper error handling. Background Two years at HarperCollins owning the advertising system behind £12.5m in annual revenue, plus company-wide LLM rollouts including manuscript analysis that cut editorial review time by 70%. Three years teaching data science, so I can explain technical decisions to non-technical stakeholders. I work end to end, from scoping and architecture through delivery and iteration, with clear communication throughout.

OVERVIEW: I build AI systems that extract structured intelligence from business documents — not chatbot wrappers. My background is unusual: CFA charterholder, former arbitrage trading desk developer, now dev team lead at a major investment bank. I've spent years building production infrastructure across finance, real estate, and enterprise software. What I build now: • Document intelligence pipelines — upload PDFs, ask questions in plain English, get structured answers with source citations and confidence scores • RAG systems — extraction, chunking, vector search, LLM synthesis, evaluation (RAGAS) • Multi-provider LLM integration — Anthropic, OpenAI, Groq, Ollama — with automatic failover and cost optimisation • Full-stack Python platforms — FastAPI backends, production deployment, cloud infrastructure Recent work: • Built a production RAG pipeline for financial document analysis (lease agreements, facility agreements, fund documents) — PDF extraction, schema discovery, hybrid search (BM25 + vectors), LLM synthesis with source citations • Multi-provider LLM abstraction layer with rate limiting, key rotation, and graceful degradation • Enterprise-grade deployment infrastructure — blue-green deployments, agent orchestration, health monitoring Stack: Python, FastAPI, PostgreSQL, Redis, OpenSearch, Docker, DigitalOcean/AWS. LLM providers: Claude, GPT, Groq, Ollama. I work fast, I ship production code, and I don't over-engineer. If you need an AI system that actually works in a business context — not a demo — let's talk.

Data Engineer | Data Analyst | Web Scraping | Automation | Dashboards | Python | SQL I help businesses build end-to-end data systems - from data collection and storage to analysis, dashboards, and automation. With 10 years of experience across finance, insurance, real estate, and tech, I specialise in turning raw, scattered data into structured pipelines and actionable insights that improve operations and decision-making. 🔹 What I Can Help You With Data Extraction & Web Scraping - Custom web scraping (Selenium, Playwright, BeautifulSoup) - API integrations (REST, third-party platforms) - Large-scale, reliable data collection pipelines Data Engineering & Pipelines - ETL / ELT pipelines - Data cleaning and transformation - Database design (PostgreSQL, BigQuery, NoSQL) - Data warehousing and optimisation Data Analysis & Insights - Exploratory data analysis (EDA) - Trend detection and anomaly detection - Business insights and reporting Dashboards & Visualisation - Interactive dashboards (Streamlit, Dash, Power BI) - KPI tracking and operational reporting - Real-time data monitoring Automation & Workflow Optimisation - Process automation (Python, APIs) - CRM and system integrations (GoHighLevel, Vicidial, etc.) - Reducing manual work and improving efficiency Machine Learning & NLP (when needed) - Predictive models - Text analysis and sentiment analysis - LLM integrations 🔹 Tech Stack Python | SQL | Pandas | Polars | FastAPI | PostgreSQL | BigQuery | Streamlit | Dash | Selenium | Playwright | APIs | Cloud (GCP) 🔹 What You Can Expect Clean, maintainable, production-ready code Clear communication and fast turnaround Solutions designed for real business use, not just analysis Focus on automation, scalability, and reliability If you need help with data pipelines, scraping, dashboards, or automation, feel free to reach out. I’m happy to discuss your project and suggest the best approach.