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If you need healthcare data pipelines, analytics systems, AI-powered workflows, or biostatistical analysis, I can help you develop a reliable solution tailored to your project. I combine healthcare data engineering and biostatistics with clinical research experience demonstrated by 62 medical articles indexed in PubMed. I CAN HELP YOU WITH: Data Engineering & AI • Build and maintain production ETL/ELT pipelines • Develop and manage Apache Airflow and Google Cloud Composer workflows • Design BigQuery pipelines, SQL transformations, and analytics systems • Integrate EHR platforms, third-party APIs, and external data sources • Automate manual file transfers and system-to-system data movement • Extract structured clinical data from PDFs, scanned documents, and laboratory reports • Build controlled AI-agent workflows for healthcare data • Automate KPI dashboards and recurring reports • Develop machine-learning solutions for healthcare analytics Biostatistics & Clinical Research • Analyze clinical, observational, and survey data using Python or IBM SPSS • Prepare descriptive statistics and hypothesis tests • Perform linear and logistic regression analyses • Conduct survival analysis • Apply parametric methods, including t-tests, ANOVA, ANCOVA, MANOVA, and repeated-measures ANOVA • Apply nonparametric methods, including Mann–Whitney U, Kruskal–Wallis, Wilcoxon signed-rank, and Friedman tests • Interpret statistical findings in their clinical and scientific context • Create publication-ready tables, figures, and statistical summaries • Review statistical methods and results sections for manuscripts • Communicate findings clearly to clinicians, researchers, and nontechnical stakeholders Send me a brief description of your project. For statistical work, you may also share the research question, dataset structure, or a de-identified sample. I can provide a complimentary preliminary scope review and suggest practical solution options. If one of those approaches fits your needs, we can then discuss the implementation details. WHY WORK WITH ME? My background combines production data engineering with genuine clinical and research experience. Before moving into technology, I worked as a medical doctor and researcher who published 62 medical articles indexed in PubMed. This experience enables me to understand both the technical architecture and the real-world meaning of healthcare data. I know that a statistically correct result must also be clinically meaningful and that a technically functional system must be reliable, maintainable, and appropriate for its healthcare environment. I can work directly with medical terminology, research questions, clinical outcomes, and study documentation without requiring clients to translate the clinical context into purely technical language. Selected experience: • Built AI-assisted workflows that extract laboratory data from unstructured PDF reports and load structured results into BigQuery • Developed and maintained healthcare data pipelines integrating multiple EHR and external data sources • Optimized Google Cloud Composer workloads to improve reliability and control infrastructure costs • Developed machine-learning and anomaly-detection pipelines for IoT monitoring data • Conducted biostatistical analyses for clinical research and peer-reviewed publications Core technologies: Python, SQL, Apache Airflow, Google Cloud Composer, BigQuery, dbt, GCP, Docker, Pandas, NumPy, scikit-learn, XGBoost, LangChain, Agno, Kafka, REST APIs and IBM SPSS.

Your business runs on data — leads, contacts, records — but it's scattered across sites, sheets and tools, and someone on your team is still copying it by hand. I build the automated systems that make that work disappear. ⭐ Top Rated · 100% Job Success · $10K+ Earned · 600+ hours delivered Hi, I'm Caner 👋 My foundation is in mathematics and data science — it's how I first learned to code — and it grew into building production data & automation systems. That's how I work: precise, structured, and built so nothing breaks silently. 🚀 A recent result: I built a custom extraction system that collected and enriched 100,000+ contacts across 19 data fields — 1.9 million data points. By hand, that's over 2 years of full-time work. I engineered the extraction logic for each source and solved the anti-bot challenges directly, using AI agents only where deterministic code fell short (like email discovery) — keeping running costs low. Other work: ✅ Verified B2C lead-list systems (Ontario, Canada) — 5-star rated ✅ An AI Agent web scraper a client called "the most skilled and detailed developer I've worked with" ✅ Currently building an ongoing researcher contact-enrichment pipeline (Python, Supabase, APIs, scraping) The problem I usually solve: Data lives in ten places. Leads slip between channels. Reports are built by hand every week. You know time and money are leaking somewhere — but the current setup makes it hard to see where. I turn that mess into one system that collects, cleans, enriches and moves your data automatically. 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗜 𝗯𝘂𝗶𝗹𝗱: • AI agents & LLM workflows — automations that classify, summarise, enrich and act on your data (Python, OpenAI/Claude APIs) • Automation & ETL pipelines — lead gen → enrichment → CRM/Sheets → outreach (n8n, Python) • Data analysis & dashboards — clean, structure and analyze data into clear insights and live dashboards (Pandas, SQL, PostgreSQL, Supabase), backed by a strong mathematical foundation • Data collection & scraping — when a project needs external data, resilient anti-bot scrapers (Playwright, Selenium) feed clean, verified data straight into the pipeline ⚙️ I build what actually fits — not the flashiest option. Fully "hands-off" data systems only work when the source is fixed and stable. When sources change or block you, it takes real engineering — the right architecture, an anti-bot strategy where needed, and AI used only where it genuinely adds value. Sometimes the right answer is an AI agent; sometimes it's a cleaner pipeline or one source of truth instead of five tools. I'll tell you honestly which one your project needs — and keep your costs down while I'm at it. 🏗️ Built to maintain, not to throw away. Each data source is engineered as a reusable module — not a disposable one-off script. When target sites change their structure (which they do every few months), refreshing the whole system takes days instead of a rebuild from scratch: what would be a 3–4 month rebuild becomes a 1–2 week update. That's what makes it viable for large companies running data operations at scale — no constant babysitting, low long-term maintenance cost. Why clients keep me: ✅ Fault-tolerant by design — no silent failures, no data loss, no schema drift ✅ 0–4 hour response time and clear, honest communication ✅ Delivered exactly what's promised, on time What clients said: "…the most skilled and detailed developer I have worked with." "He goes above and beyond and always delivers!" If your data or lead process is creating manual work or hiding revenue somewhere it shouldn't — send me a message and let's map out the system that fixes it. 🚀

I build code-first Python data systems that turn messy, scattered, or large datasets into clean, reliable, and usable workflows. ⭐ I am a Top Rated freelancer with 100% Job Success, several thousand dollars earned, and hands-on experience across data engineering, ETL pipelines, API integrations, data processing, backend development, automation, databases, and AI-ready datasets. My work usually involves: 🔹 Collecting, cleaning, transforming, and structuring data from files, APIs, databases, and external sources 🔹 Building reliable Python pipelines for repeatable data processing, exports, reporting, and workflow automation 🔹 Designing database-backed workflows for storing, querying, organizing, and exporting structured data 🔹 Preparing structured datasets and knowledge bases for analytics, machine learning, NLP, or LLM/RAG systems 🔹 Creating custom backend tools, data workflows, and lightweight dashboards when the project needs more than a one-time script Recent projects included processing and structuring large volumes of data, cleaning and automating tens of thousands of data records, building data-driven systems, exporting datasets from databases, and developing AI-ready data workflows for real-world applications. I focus on clear communication, careful implementation, and practical systems that are easy to understand, maintain, and extend.

I build production-ready AI applications that help businesses automate workflows, work with their internal knowledge, and reduce manual work. My main focus is LLM applications, AI Agents, RAG systems, and custom LLM solutions. I can take an AI idea from an initial concept to a working prototype or production-ready application. What I can build for you AI Agents & Agentic Applications * AI agents that use tools, APIs, databases and external services * Multi-step agentic workflows with LangGraph * MCP integrations and MCP-based tool usage * Business process automation * AI assistants that can actually perform tasks, not just generate text RAG & AI Chatbots * Document-based AI assistants * RAG over PDFs, websites, databases and internal documentation * Semantic and hybrid search * Vector databases and retrieval pipelines * Evaluation and optimization of RAG quality * Private enterprise knowledge assistants LLM Applications * Custom AI assistants and copilots * LLM-powered backend services and APIs * OpenAI and open-source LLM integrations * Structured outputs and tool calling * AI-powered automation and internal tools Local & Private AI * Run LLMs locally using Ollama or vLLM * Open-source model deployment and optimization * Reduce dependency on expensive API calls * Keep sensitive business data inside your infrastructure Datasets & Fine-tuning * Dataset preparation for LLM training * Instruction and conversational datasets * Data cleaning and preprocessing * LoRA / QLoRA fine-tuning * Fine-tuning open-source LLMs with Unsloth Why work with me? I have 10+ years of software development experience and extensive experience in machine learning, NLP and LLM-based applications, including work in a large financial organization. I don't approach AI projects as pure research. My goal is to understand the business problem, choose the simplest effective architecture, and deliver a working solution that can actually be used. I'm comfortable working directly with clients: discussing requirements, designing the architecture, making technical decisions, and implementing the solution end-to-end. Tech Stack Languages: Python LLM / AI: OpenAI, Hugging Face, Ollama, vLLM, Unsloth Agents: LangGraph, LangChain, MCP, LlamaIndex RAG: Qdrant, FAISS, ChromaDB, hybrid search Backend: FastAPI, Docker Cloud: AWS AI Development: rapid prototyping, AI-assisted development, vibe-coding workflows If you have an AI idea, an existing prototype that needs to be improved, or a business workflow you'd like to automate, send me a message and let's discuss how to build it.

I write clear, accurate, and engaging technical content about AI, data science, machine learning, and software products. With 3+ years of hands-on experience as a Data Scientist and AI Engineer, I understand the technologies I write about. I can turn complex technical concepts, product features, and research into content that is easy to follow without oversimplifying the subject. I can help you with: • Technical blog posts and long-form articles • AI, machine learning, data science, and analytics content • Product tutorials, explainers, and use cases • Developer-focused and thought-leadership content • Research-based articles and technical editing • SEO-friendly content for technical audiences My background includes machine learning, NLP, LLM applications, AI agents, data analytics, OCR automation, customer journey analysis, and cloud-based AI systems. I have written about topics such as AI testing agents, LLM systems, knowledge graphs, machine learning workflows, and data products for technical companies and publications. You can expect well-researched content, clear communication, and writing that is both technically reliable and enjoyable to read.

Automated vulnerability scanners miss critical business logic flaws and flood reports with false positives. I deliver deep manual penetration testing, protocol-level auditing, and custom offensive tooling to identify and neutralize high-risk attack paths before real-world adversaries exploit them. Certified Ethical Hacker (CEH v13), ISO/IEC 27001 Lead Auditor, and Top 0.55% Ranked Practitioner on Hack The Box. I help engineering teams, SaaS platforms, and enterprise infrastructures secure their applications, networks, and cloud environments against sophisticated threat actors. CORE SECURITY SERVICES & DELIVERABLES • Web Application & API Penetration Testing: Deep manual assessments across REST/GraphQL APIs, OAuth/JWT authentication flaws, complex business logic bypasses (IDOR/BOLA), and OWASP Top 10 vulnerabilities. • Active Directory & Cloud Infrastructure: Domain escalation auditing, Kerberoasting/AS-REP roasting, NTLM Relay vectors, ADCS certificate misconfigurations, and hybrid Entra ID (Azure AD) attack path mapping. • Network & Linux Infrastructure Hardening: Kernel stack tuning (sysctl), ingress traffic filtering (nftables/iptables), DDoS mitigation, and exposed surface lockdown. • Executive & Remediation-Focused Reporting: Actionable, risk-prioritized reports formatted to NIST SP 800-115 and PTES standards—complete with CVSS v3.1 scoring, reproducible PoC chains, and regulatory alignment (GDPR, NIS2, ISO 27001). PROPRIETARY TOOLING & CUSTOM AUTOMATION (NOEMVEX SUITE) When off-the-shelf commercial scanners fail in non-standard or heavily fortified architectures, I build bespoke, object-oriented Python security engines to conduct precision assessments: • APEX-PREDATOR: High-speed Active Directory auditing engine automating unauthenticated SMB signing verification, Zerologon analysis, and Kerberos ticket validation. • WEB-ARCHITECT: Specialized client-side parser for JavaScript deobfuscation, hidden endpoint discovery, and automated PII/credential leak detection. • CHRONOS: Reconnaissance and attack surface mapping framework utilizing Shannon Entropy algorithms for cryptographic key discovery and cloud asset hijacking validation. VERIFIED CREDENTIALS & AUDIT STANDARDS • EC-Council: Certified Ethical Hacker (CEH v13) • ISO/IEC 27001: Information Security Management System (ISMS) Lead Auditor • Cisco: Cybersecurity Defense Analyst (SOC Triage, Splunk SPL & PEAK Threat Hunting) • Qualys Certified Specialist: VMDR, Policy Compliance, CSAM & QQL • Rank: Top 0.55% Globally (Pro Hacker Tier) on Hack The Box • Methodologies: NIST SP 800-115, OWASP WSTG, PTES, and OSSTMM Available for scoped penetration tests, fixed-price security assessments, and custom offensive tool development.