I bridge the gap between traditional backend architecture and modern AI implementation. With 2.5 years of professional experience moving from a self-taught developer to a Data Analyst, I specialize in building scalable systems that don't just "work" but actively optimize your business operations. Currently pursuing a B.S. in Data and AI Engineering at Universidad Santo Tomás, I offer a unique hybrid of web development and data science. Whether you need a high-performance API in NestJS, a complex automated workflow in n8n, or a production-ready AI Agent, I deliver clean, documented, and containerized code. Core Expertise: -Backend & APIs: Expert-level development using Node.js (NestJS, Express) and Python (Django, Flask). -AI & Automation: Architecting AI Agents and Chatbots with n8n, Rasa, and the Hugging Face ecosystem. -Prompt Engineering: Deep research in LLM optimization. I have actively trained corporate teams on effective prompting and AI integration strategies. -Data Science: Production-level data analysis and NLP using Pandas, NumPy, Seaborn, and SpaCy. -Modern Frontend: Professional builds with Next.js, Angular, and Vue. Technical Toolkit: -Databases: SQL (PostgreSQL, MySQL), MongoDB, SQLite. -DevOps: Docker & Docker Compose (Containerization), Git/GitHub (Version Control). -Testing: Advanced API debugging with Postman and Insomnia. Why Hire Me? -C2 English Proficiency: I communicate at a native/bilingual level. No language barriers, just technical clarity. -Academic Backing: I am formally studying the latest breakthroughs in AI Engineering, ensuring your project uses modern best practices. -Results-Oriented: I don’t just write code; I build tools that save time and reduce manual workload. Availability: Currently accepting contract-based projects to align with my academic specialization.

Professional Mobile App Developer & Consultant | 50+ Apps Launched | 4+ years of experience Hello! I'm 𝗦𝗲𝗻𝗶𝗼𝗿 𝗠𝗼𝗯𝗶𝗹𝗲 𝗔𝗽𝗽 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 with 𝟰+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 in building Mobile Apps using React Native, Flutter, Swift, Java and Kotlin, My expertise lies in building responsive and complex apps that provide a seamless user experience. 🚨 Why Hire Me : ✅ 4+ year of Mobile App Industry Experience. ✅ Client-Centric Approach ✅ Custom Solutions and High-Quality Code ✅ Proficiency in Modern Technologies ✅ Front-end & Backend Mobile App Development ✅ End-to-End Mobile App Development 🌟 My Skills and Experience: - Cross-Platform Development: Expert in React Native, Flutter and Kotlin, following architectures like MVP and MVVM. - API Integration: Skilled in integrating RESTful APIs, GraphQL, and databases like Supabase, Firebase, AWS Amplify, MongoDB Realm, and Hasura. - Mobile App UI/UX: Proficient in Material Design, Jetpack Compose, and custom UI/UX design to create intuitive and visually appealing interfaces. - State Management: Experienced in Provider, Riverpod, Bloc/Cubit, and Redux for effective state management in Flutter & React Native apps. - Database Management: Knowledgeable in working with MySQL, SQLite (Local Storage), MongoDB, and Firebase Realtime Database, as well as local storage solutions like SharedPreferences, Secure Storage, and Hive. - Mobile App Monetization: Extensive experience with App Subscriptions, In-App Purchases, and Payment Gateway Integration. - Mobile App Performance Optimization: Experience in memory management, battery optimization, lazy loading, offline caching, and profiling tools like Android Profiler, Xcode Instruments, and Firebase Performance Monitoring. - Version Control & Project Management: Skilled in using Git, GitHub, Bitbucket, and project management tools like Jira, Trello, and Asana. ✅ My Achievements ➜ Quick Mart (E-commerce Mobile App): Developed a feature-rich Android and iOS e-commerce app that resulted in a 30% increase in client sales within the first six months post-launch, driving significant revenue growth for the business. ➜ Food Delivery Mobile App: Built a scalable Android and iOS food delivery app, streamlining order management and increasing user retention by 25% through a personalized ordering experience. ➜ Event Management Mobile App: Successfully developed an end-to-end event management app for Android, enabling users to seamlessly plan, schedule, and track events, improving event coordination efficiency for clients by 40%. ➜ Ride Sharing Mobile App: Created a robust ride-sharing app for Android and iOS, optimizing real-time tracking and in-app communication, which increased ride-booking efficiency by 50% and improved the user rating to 4.7/5. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗶 𝗨𝘀𝗲𝗱: 👉Native Android Mobile app Development 👉Hybrid Mobile App Development 👉React Native, Flutter, Kotlin, Swift, Java 👉Node JS, 👉Express JS 👉MongoDB 👉Firebase 👉Android SDK 👉Google Admob 👉JSON 👉XML 👉Rest API's 𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗦𝗲𝗻𝗶𝗼𝗿 𝗠𝗼𝗯𝗶𝗹𝗲 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘆𝗼𝘂𝗿 𝗱𝗿𝗲𝗮𝗺 𝗔𝗽𝗽, 𝗜 𝗮𝗺 𝗲𝘅𝗰𝗶𝘁𝗲𝗱 𝘁𝗼 𝗯𝗲 𝗮 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺 𝗮𝗻𝗱 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲 𝘁𝗼 𝘁𝗵𝗲 𝘀𝘂𝗰𝗰𝗲𝘀𝘀 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁. Check my Portfolio 🚀🚀 Thanks, Mobile App Developer Ubaid ur Rahman

I build intelligent systems that work — at scale, in production, and with measurable results. With 5+ years of hands-on experience across machine learning, deep learning, and Python automation, I specialize in architecting end-to-end AI solutions: from raw data ingestion and model training to containerized deployment and real-time monitoring. Whether you need a predictive model, an intelligent scraping system, or a fully automated workflow, I deliver production-grade work not prototypes. What I build: — ML & Deep Learning models (TensorFlow, PyTorch, Keras, Scikit-learn) serving thousands of daily predictions — Intelligent automation systems that eliminate repetitive workflows and cut manual effort by up to 80% — Web scraping infrastructure at scale using Scrapy, BeautifulSoup, and Selenium — processing millions of data points monthly — NLP pipelines and custom chatbots powered by OpenAI API, LangChain, SpaCy, and NLTK — Computer vision solutions for inspection, classification, and quality control — Scalable data pipelines on PostgreSQL, MongoDB, BigQuery, and Apache Airflow handling TB-scale datasets — Cloud-deployed ML systems on AWS SageMaker, Google Cloud AI, and Docker/Kubernetes Industries I've served: FinTech · Healthcare · E-commerce · SaaS · Manufacturing · Real Estate · Supply Chain · Marketing Tech I work with startups moving fast, agencies scaling client delivery, and enterprises modernizing their data operations. If your project demands technical depth, clean architecture, and reliable execution let's talk.

Greetings, I’m a senior full-stack engineer with 12+ years of experience building real, production systems that people actually rely on. Most of my work is in SaaS, fintech, healthcare, and AI-powered products — the kind of software that has to be fast, stable, and boringly reliable (in a good way). On the backend, I work mainly with Python (FastAPI, Django) and Node.js (NestJS). I design clean APIs, background processing, and scalable services that don’t fall apart under load. On the frontend, I build modern web apps with React and Next.js that are fast, maintainable, and easy for users to live in every day. I’ve spent years working with remote teams in the US, Europe, and Australia, owning features end-to-end — from system design to deployment and long-term maintenance. I’m comfortable in AWS, ship with Docker, and care a lot about code quality, performance, and not creating tech debt that haunts the next engineer. Clients usually describe me as easy to work with, dependable, and someone who actually finishes what they start. I ask good questions, communicate clearly, and don’t disappear when things get messy. If you need someone who can take ownership, ship clean solutions, and make your product more stable and easier to grow — I’m your guy.

Greetings! I specialize in AI & Machine Learning, Data Science, and MLOps, crafting scalable solutions that turn data into powerful insights and real-world impact. Skills: 🎯 Highly skilled in Python, with extensive experience in machine learning, deep learning, and AI. 🎯 Proficient in data extraction using Scrapy and BeautifulSoup. 🎯 Experienced in working with NLP tasks using spaCy, NLTK, and Hugging Face. 🎯 Skilled in Generative AI and using models like Transformers, DALL-E, CLIP, Stable Diffusion, and Vision Transformers (ViT). 🎯 Advanced in machine learning algorithms, including XGBoost, LightGBM, Scikit-Learn, and TensorFlow. 🎯 Highly skilled in working with time series data and models like LSTM, Pandas, and XGBoost. 🎯 Proficient in Data Science and Data Visualization, with hands-on experience in Pandas, Numpy, Matplotlib, Seaborn, Plotly, and Dask. 🎯 Experienced in using MLOps tools like MLflow, DVC, TensorBoard, and BentoML for model management and deployment. 🎯 Proficient in SQL & NoSQL databases, including PostgreSQL, MySQL, and MongoDB. 🎯 Skilled in cloud computing and deployment, including AWS, Docker, Kubernetes, and SageMaker. 🎯 Skilled in CI/CD practices, version control using Git and GitHub. 🎯 Comfortable working on both Linux (Ubuntu) and Windows Operating Systems. Data Exploration & Visualization: 🎯 Streamlit for creating dynamic data applications. 🎯 Power BI and Tableau for building interactive and professional dashboards. Tools: 🎯 VSCode, Jupyter Notebook, GitHub, Trello, Microsoft To-Do, Teams, Zoom, and Slack for efficient collaboration and project management.

I’m Ahmad Zafar Khan, an AI Engineer who builds real, production-ready AI systems, not demos or experiments that never ship. ⚠️ Note on Job Success Score: My current 79% JSS is due to a single fraudulent client incident. All other projects were delivered successfully with strong outcomes and client satisfaction. I work at the intersection of LLMs, RAG, multi-agent systems, and software engineering, helping startups and companies turn AI ideas into systems that scale, integrate cleanly, and deliver measurable business impact. I own the full lifecycle: architecture, development, deployment, and iteration in production. 🧠 What I Do Best: ⚙️ AI Systems & LLM Engineering: 🔹 LLM fine-tuning and optimization (GPT, Claude, Mistral, LLaMA) using LoRA, PEFT, QLoRA 🔹 RAG pipelines with LangChain, LlamaIndex, LangGraph 🔹 Vector databases: Pinecone, FAISS, Weaviate, Chroma 🔹 Multi-agent systems with tool calling, memory, and orchestration 🔹 Secure integration with internal data, APIs, and enterprise systems ☁️ MLOps & Infrastructure: 🔹 Production APIs with FastAPI, Docker, Kubernetes 🔹 CI/CD pipelines using GitHub Actions and Terraform 🔹 Cloud deployments on AWS, GCP, and Azure 🔹 GPU-optimized inference for low-latency workloads 🔹 Model monitoring, retraining, and rollback strategies 🔹 Secure systems with OAuth2, encryption, and access control 🔁 Automation & Agentic Workflows: 🔹 Business automation using n8n, Zapier, Make 🔹 AI agents for customer support, scheduling, CRM, HR, and ops 🔹 Integrations with HubSpot, ClickUp, Slack, Stripe 🔹 Human-in-the-loop workflows and feedback-driven improvement 🧩 Full-Stack Engineering: 🔹 Frontend: React, Next.js, TypeScript, Tailwind, shadcn/ui 🔹 Backend: FastAPI, Django, Flask, Node.js 🔹 Mobile: Flutter, React Native 🔹 Databases: PostgreSQL, MongoDB, Redis, Neo4j 🔹 Payments & APIs: Stripe, PayPal, GraphQL, Firebase 🛠️ What I’ve Built: ✅ RAG-powered knowledge assistants and internal AI copilots ✅ Multi-agent LLM systems (LangGraph, CrewAI, AutoGen) ✅ AI-powered SaaS dashboards and admin portals ✅ Document parsing and semantic search engines ✅ Workflow automation platforms (CRM, HR, Finance, Ops) ✅ Cloud-native AI APIs with GPU-backed inference ✅ Voice and chat AI agents for real-time interaction 🚀 Why Clients Hire Me: ✨ 20+ AI projects delivered across startups, SaaS, and enterprise teams ✨ End-to-end ownership from architecture to deployment ✨ Domain-specific AI for legal, healthcare, and finance use cases ✨ Strong experience with RAG and automation-heavy systems ✨ Cloud-native mindset with scalable, reliable infrastructure ✨ Clear communication, strong documentation, fast iteration 🧪 Tech Stack Snapshot: 🧠 LLMs: GPT-4, Claude, Mistral, LLaMA, Hugging Face 📦 Frameworks: LangChain, LangGraph, LlamaIndex 📊 ML: PyTorch, TensorFlow, Scikit-learn, SpaCy, OpenCV ☁️ Infra: Docker, Kubernetes, Terraform, AWS, GCP, Azure 🔄 Automation: n8n, Zapier, Make 🗄️ Databases: PostgreSQL, MongoDB, Redis, Neo4j 🌐 Web & Mobile: React, Next.js, FastAPI, Django, Flutter 🎯 Ideal Projects: 🚀 RAG-powered platforms and internal AI systems 🚀 Agentic AI workflows and automation-heavy products 🚀 SaaS products integrating LLMs into existing architectures 🚀 Rapid MVPs that need to grow into production systems 🚀 Founders who care about reliability, not hype 🤝 Let’s Build Something Real If you need an engineer who can design, build, and deploy AI systems that actually hold up in production, I’d love to help. Let’s turn your idea into a scalable AI product that delivers real results.

I’m Okafor Chibuzor Authur, an AI Engineer specializing in LLM systems, Retrieval-Augmented Generation (RAG), and multi-agent AI architectures. I build production-grade AI platforms and scalable automation workflows that help businesses unlock value from large-scale data, streamline decision-making, and operationalize AI reliably. What you get working with me is a partner who can take an AI solution from concept to production using proven, production-ready patterns. I design systems that are scalable, operationally practical, and aligned to measurable business outcomes. How I help you increase ROI and reduce cost 1. Automate complex workflows that would otherwise require significant manual effort and headcount. 2. Improve retrieval accuracy and response quality with RAG (document chunking, embeddings, retrieval, and scoped question answering), reducing time spent searching, verifying, and rewriting information. 3. Enable intelligent, scalable operations through multi-agent workflows (including LangGraph-based orchestration), so repetitive and high-volume tasks are handled faster and more consistently. 4. The result is faster turnaround times, reduced operational overhead, and better utilization of your existing business data, translating into stronger output per dollar spent. What I build and deliver 1. RAG-powered document intelligence systems: upload documents, extract text, chunk and embed into vector stores, retrieve relevant context, and generate accurate AI answers and drafts. 2. Agentic automation workflows: multi-step systems where AI agents can reason, collaborate, and take structured actions (LangGraph-based workflows). 3. Production AI backends and platforms using FastAPI, PostgreSQL (pgvector), Redis, and Celery for asynchronous and scalable processing. 4. Deployable solutions to AWS, GCP, Vercel, and Docker-based infrastructure designed for real-world usage. Where I’ve delivered value I’ve delivered high-impact AI solutions across e-commerce, customer support, and internal automation, and I’m comfortable working under strict client confidentiality when needed.

• Languages: C, C++, MATLAB, Node.js, Python, R, REST, SPARQL, SQL, OWL • Frameworks: FastAPI, Flask, Gradio, Keras, NLTK, NumPy, Pandas, PyQt, PyTorch, React, Scikit-Learn, SpaCy, Streamlit, TensorFlow • Tools: Apify, ComfyUI, Crew.ai, Docker, GraphDB, Jupyter, Kubernetes, LangChain, LlamaIndex, MySQL, n8n, Protege, PyCharm, Salesforce, Twilio, Visual Studio, Zapier • Platforms: AWS (EC2, Amplify, Lambda, Bedrock, Sagemaker), Azure, GCP (Firebase, Vertex), Linux, RunComfy, Snowflake (Cortex, Snowpark), Windows • Soft Skills: Agile, Communication, Communication Management, Decision Making, Innovation, Managing Innovation, Planning and Scheduling, Product Development, Quality Management, Resource Management, Scrum, Stakeholder Management, Strategic Thinking, Technical Leadership

𝗕𝗶𝗼𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝘆 & 𝐆𝐫𝐚𝐩𝐡-𝐑𝐀𝐆 𝐍𝐞𝐨𝟒𝐣 | 𝗖𝘆𝗽𝗵𝗲𝗿 𝗔𝗴𝗲𝗻𝘁 | 𝗣𝗶𝗽𝗲𝗰𝗮𝘁 | 𝐀𝐳𝐮𝐫𝐞 𝐒𝐞𝐚𝐫𝐜𝐡 | 𝗥𝗮𝗴 𝗙𝘂𝘀𝗶𝗼𝗻 | 𝗥𝗲-𝗿𝗮𝗻𝗸𝗶𝗻𝗴 | 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 | 𝐋𝐚𝐭𝐞 𝐂𝐡𝐮𝐧𝐤𝐢𝐧𝐠 | 𝐓𝐨𝐆 (𝐓𝐡𝐢𝐧𝐤-𝐎𝐧-𝐆𝐫𝐚𝐩𝐡) | 𝗥𝗔𝗚 𝗘𝘃𝗮𝗹 | 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐆𝐫𝐚𝐩𝐡 𝐀𝐏𝐈 I specialize in developing RAG and AI Agent systems with 15+ years of full-stack experience using LangChain, LangGraph, FastAPI, and vector databases (Qdrant, Pinecone, FAISS etc). For data ingestion, I build end-to-end pipelines supporting multi-format sources (PDF, DOCX, CSV, Excel, websites), structured cleaning with spaCy, Textacy & CleanText, web scraping via Playwright, BeautifulSoup & Jina Reader, Overlap Late Chunking for retrieval accuracy, and Microsoft Graph API integration for SharePoint/OneDrive across Microsoft 365.I also build real-time Voice AI agents using Pipecat with full STT → LLM → TTS streaming pipelines. My retrieval expertise covers Re-ranking (Cohere, FlashRank, Jina), dense/sparse/hybrid search, RAG Fusion, Semantic Caching, contextual compression, custom output parsers, LLM Token tracing, and RAGAS-based evaluation. I am a 𝐍𝐞𝐨𝟒𝐣 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐞𝐝 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 specializing in Graph RAG, graph data modeling, Cypher queries, and domain ontology alignment. For graph ingestion, I have developed knowledge graph pipelines using GraphTransformers and NLP libraries for entity & relation extraction, aligned with domain-specific ontologies. For graph retrieval, I have implemented Graph Traversal, vector search, Think-On-Graph (ToG) reasoning, and Cypher Agents (generation, validation, correction, execution) leveraging LLMs for answers. Front End experience with TypeScript, Vue.js Composition API, Quasar Framework. I have a sharp eye for detail and quality and have experience of Software Reengineering. I am a self motivated individual who is both deadline focused and thorough in my approach to work. -------------------𝐏𝐫𝐨𝐯𝐞𝐧 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭------------------- 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐑𝐀𝐆 & 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 • Implemented RAG with multiple data formats (PDF, DOCX, CSV, Excel, TXT, websites etc.) • Enhanced retrieval techniques using RAG Fusion with multiple re-rankers (Cohere, FlashRank, Jina) • Applied optimization strategies like Prompt Caching, Semantic Caching with vector databases • Context-aware chunking is implemented by "Overlap Late Chunking" to improve retrieval accuracy • Conducted RAG evaluations using RAGAS for quality assessment and benchmarking • Built structured web scraping and cleaning pipelines using Playwright, BeautifulSoup, Jina Reader, Textacy, CleanText, spaCy etc. • Implemented dense, sparse, and hybrid search for advanced similarity search and optimal retrieval • Implemented LLM Token Tracing for monitoring LLM cost per user • Implemented custom output parsers for specialized formatting • Integrated Microsoft Graph API to fetch and process data from SharePoint and OneDrive across Microsoft 365 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐆𝐫𝐚𝐩𝐡 & 𝐆𝐫𝐚𝐩𝐡𝐑𝐀𝐆 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 • Built Neo4j GraphRAG system with Graph Traverse and vector search capabilities • Created knowledge graphs aligned with domain-specific ontologies including bio-medical Ontology, using transformers, custom logic and detailed instruction-based prompts. • Developed Cypher Agents with LangGraph for Cypher generation, validation, correction, and execution • MS GraphRAG solutions with LanceDB and Parquet files, search and Indexing ,incremental indexing. • Successfully migrated MS GraphRAG Parquet files to Neo4j (KG) database systems 𝐋𝐋𝐌 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈 • Designed LangGraph Agent architectures for multi-step reasoning workflows • Built multi-agent systems with specialized roles • Applied advanced prompt engineering with few-shot learning and context window optimization • Developed real-time Voice AI agents using Pipecat for low-latency conversational interactions • Implemented streaming speech-to-text → LLM reasoning → text-to-speech pipelines 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 • Backend Development: Python, FastAPI for scalable services • Vector Database Integration: Qdrant, Faiss, LanceDB for efficient similarity search • Hybrid Application Development: Cross-platform solutions with Quasar Framework • Mobile Application Development: Expertise with Capacitor and Electron frameworks 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: - 𝐀𝐈/𝐋𝐋𝐌: Langchain, LangGraph, LlamaIndex, OpenAI, Claude - 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: Neo4j, Qdrant, FAISS, LanceDB, Pinecone, Chroma - 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈: Pipecat, Real-time Voice Agents, STT/TTS streaming pipelines - 𝐖𝐞𝐛 𝐂𝐫𝐚𝐰𝐥𝐢𝐧𝐠: FireCrawl, Jina, Puppeteer, Scrapy, Playwright, Beautiful Soup - 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: Llama Parse, Document Loaders, spaCy, Textacy

⭐️ Top Rated - Top 10% of Talent on Upwork 🕒 7+ Years of Experience in Data Science & Business Intelligence ✅ Successfully Delivered 133+ Projects ✅ Supported Over $2M+ in Data-Driven Business Decisions ✅ Excelling in delivering Fortune 500-scale Projects Hi! I'm a Senior Data Scientist, Data Analyst, and Power BI Developer with 7+ years of experience turning messy data into clean insights, reliable Machine Learning models, and deployment-ready AI solutions for startups, SMEs, and enterprise teams. I work as a hands-on data & AI partner from exploratory data analysis and statistical modelling to production ML pipelines, Power BI dashboards, and Deep Learning workflows. Send me a dataset, notebook, GitHub repo, or paper and I'll turn it into a working, documented solution. ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 Accomplishments ━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⭐ Top Rated — Top 10% of Data Science & Analytics talent on Upwork ⭐ 133+ projects across Data Science, ML, Deep Learning, Data Analysis & Power BI ⭐ $2M+ in data-driven business decisions supported across finance, healthcare & SaaS ⭐ Fortune 500-scale BI pipelines, ML solutions & reporting automation delivered ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 Core Services ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Data Science, Data Analysis & Statistics EDA, hypothesis testing, regression analysis, time series analysis, predictive analysis, statistical analysis, A/B testing, cohort analysis, clinical data preprocessing, medical data analysis, survey analysis, financial analysis, and business reporting — Python, R, SQL, Excel. 📈 Power BI, BI & Data Visualization Power BI dashboards, DAX optimization, Power Query, KPI systems, executive reporting, self-service analytics, ETL/ELT pipelines, data warehousing, star schema, data modeling, performance tuning, marketing analytics, financial reporting, and forecasting — Tableau, Looker Studio, Excel. 🧠 Machine Learning & Model Training Regression, classification, multi-class classification, clustering, anomaly detection, churn prediction, forecasting, recommendation systems, trading signals, risk scoring, sports prediction — feature engineering, model evaluation, explainable AI, and reproducible Python notebooks. 🤖 AI Development, Deep Learning & LLMs LLM fine-tuning, RAG chatbots, AI agents, NLP pipelines, text classification, semantic search, embeddings, TTS, text-to-image, document processing, AI simulations, multimodal AI, Deep Learning pipelines, and web app model integration — OpenAI, Hugging Face, LangChain, PyTorch, TensorFlow. 👁 Computer Vision & Image AI Object detection, object tracking, image classification, image segmentation, 2D/3D pose estimation, OCR, medical image analysis, satellite data, and COLMAP workflows — OpenCV, YOLO, PyTorch. 📡 Data Engineering, Scraping & Automation Web scraping, ETL pipelines, API integration, data cleaning, sensor data, SQL databases, and automation workflows — preparing datasets for ML, AI, and Data Science projects. 🔁 GitHub & Hugging Face Repo Reproduction Research paper implementation, repo debugging, notebook fixing, model fine-tuning, dependency resolution, and turning experimental code into production-ready solutions. ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🛠 Tech Stack ━━━━━━━━━━━━━━━━━━━━━━━━━━━ Data Science & Analytics: Python, R / RStudio, SQL, Excel, Statistics, Pandas, NumPy, Scikit-learn, SciPy, Statsmodels BI & Visualization: Power BI, DAX, Power Query, Tableau, Looker Studio, Excel Dashboards, Matplotlib, Seaborn, Plotly Machine Learning & AI: TensorFlow, PyTorch, Keras, Hugging Face, LangChain, OpenAI API, YOLO, OpenCV, spaCy, NLTK, XGBoost, LightGBM, RAG, LLM fine-tuning Data Engineering & Databases SQL Server, PostgreSQL, MySQL, ETL Development, Data Warehousing, Data Modeling, Azure Data Services, API Integration, BeautifulSoup, Scrapy ━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Hire Me For ━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Power BI dashboards, DAX, automated reporting & executive BI ✅ ML models: regression, classification, forecasting, anomaly detection ✅ LLM fine-tuning, RAG chatbots, NLP & AI app integration ✅ Computer vision: detection, segmentation, 2D/3D pose estimation ✅ EDA, statistical analysis, A/B testing & research visualisation ✅ ETL pipelines, web scraping & data engineering ✅ Research paper & GitHub/Hugging Face repo reproduction ✅ Medical AI, clinical data, sensor data & trading signal models You can send me a dataset, Excel/CSV file, database, API, sensor data, sports data, medical data, notebook, paper, GitHub repo, Hugging Face model, or incomplete codebase, and I will turn it into a clean, working, documented solution. Let's connect and make your data work for you.