I’m a GenAI, Data Science, and AI SaaS Engineer who builds production-ready AI systems—not just notebooks or demos. I help startups and teams turn ideas into working products by combining LLMs + data science + scalable infrastructure. Many AI projects fail when they meet real-world data: messy inputs, changing schemas, unclear metrics, and systems that can’t scale. I handle the full lifecycle—from data analysis and modeling to LLM/RAG development, automation, and cloud deployment—so your solution is accurate, reliable, and maintainable. What I Build 🧩 • LLM Applications: AI assistants, copilots, ChatGPT-style interfaces, domain-specific chatbots • RAG Pipelines: document ingestion → embeddings → retrieval (Pinecone/FAISS/Weaviate), re-ranking, and evaluation for accuracy • Agentic Workflows (lightweight when needed): tool-calling agents for structured tasks and integrations • Data Science Solutions: EDA, feature engineering, predictive modeling, classification/regression, forecasting, anomaly detection, A/B testing, metrics design • Data Pipelines & Analytics Backends: Python, FastAPI, Airflow, PostgreSQL; structured + unstructured data integration • Automation & Integrations: n8n/Zapier + custom Python scripts, webhooks, event-driven workflows DevOps & Scaling ⚙️ • Deployment: Docker, Kubernetes • Infrastructure: Terraform • CI/CD: GitHub Actions • Production reliability: logging/monitoring, cost control, performance optimization, secure API deployments Tech Stack 🧠 • GenAI/LLMs: OpenAI, Claude, Gemini, Llama, Hugging Face • Frameworks: LangChain, LlamaIndex • Data Science: Python (Pandas, NumPy, scikit-learn), experiment design, evaluation metrics • Backend/Data: FastAPI, PostgreSQL, Airflow • Vector DB: Pinecone, FAISS, Weaviate • Cloud/DevOps: AWS, GCP, Docker, Kubernetes, Terraform • Automation: n8n, Zapier How I Work ✅ 1. Discovery: goals, users, data sources, success metrics 2. Plan: architecture + modeling approach + milestones 3. Build: iterative delivery with clear demos and checkpoints 4. Production: testing, monitoring, deployment, documentation 5. Support: improvements, scaling, and optimization as usage grows If you need someone who can combine data science rigor with GenAI product engineering and DevOps, message me with your dataset/workflow and target outcome 💬

I build data pipelines and AI systems that turn raw data into structured insights and intelligent workflows. My focus is on strong data engineering combined with analysis, visualization, and AI integration so the data is actually usable. What I do - Data engineering pipelines (ETL/ELT, batch and real-time) - Python for data processing, automation, and AI workflows - SQL, data modeling, and query optimization - Data analysis and insights generation - Data visualization (Power BI, dashboards, reporting) - Data integration (APIs, databases, cloud systems) - RAG pipelines, LLM workflows, AI data preparation - Workflow automation and orchestration Experience - Healthcare, legal, insurance, logistics - Data-heavy systems, reporting, and automation workflows Work Examples - Built ETL pipelines connecting APIs, databases, and cloud systems - Automated data workflows to reduce manual processing - Designed dashboards for reporting and decision-making - Structured data pipelines for AI and document processing systems - Integrated multiple systems for consistent data flow How I Work - Clean, reliable data pipelines - Focus on usable data, not just movement - Systems built for analytics and AI from the start Let’s Talk If you need help with data pipelines, dashboards, or preparing data for AI, I can help. Open to a quick free consultation.

I turn messy environmental, agricultural and geospatial data into decisions. Not just maps and shapefiles, the forecast, the dashboard and the answer your team can act on. I am a Data Scientist and Forest Engineer with 10+ years of experience. I currently lead the Data Intelligence area for the Planning Advisory Department at IDR-Paraná, where my pipelines support 399 municipalities and inform an agricultural and forestry sector worth billions. In practice that means I do four things most GIS freelancers do not do together: Geospatial data engineering. Production Python + PostGIS pipelines that pull multi-source data (satellite, census, trade, land prices, field data) into clean, reproducible datasets. Scheduled and tested with GitHub Actions, not one-off scripts. Machine learning on spatial data. scikit-learn and PyTorch models for time-series forecasting, clustering and segmentation, and collaborative filtering. The “what does this mean and what happens next” layer, not just the map. Decision dashboards. Interactive Plotly/Dash and Power BI dashboards that stakeholders actually use to decide. I built Datageo Paraná, a public platform with 10 interactive dashboards spanning 30+ years of data and 400+ products (VBP, census, ComexStat, employment, land prices, forestry prices). Domain depth. Forestry, agribusiness, sustainability and public-sector analytics. I have led FSC- and NR-31-compliant operations across multi-million-hectare projects, so I understand the data and the decisions behind it. What you get when you hire me: a clear scope up front, fast and direct communication, a documented methodology, original analysis (never recycled or plagiarized), and a full handoff of the maps, the validated pipeline and the code. You own everything at the end. Tools: Python, PostGIS / PostgreSQL, QGIS, scikit-learn, PyTorch, Plotly/Dash, Power BI, Supabase, GitHub Actions, GDAL/GeoPandas/Shapely/rasterio, SQL. Good fit if you need: satellite / remote-sensing analysis, geospatial web scraping and data acquisition, spatial data pipelines, forecasting or segmentation on geographic data, interactive geo dashboards, or forestry / agribusiness / environmental decision analytics. If you have geographic data and a decision to make, message me. I will tell you honestly whether I am the right fit and what the smallest useful first step looks like.

Hello, I'm Anup Patil, an AI-powered Web Scraping & Data Engineer with 12+ years experience in building intelligent data extraction systems, automation pipelines, and dashboards for AI/ML and business intelligence projects. Today, I leverage modern AI coding tools (Codex, Claude, Cursor, Copilot) together with strong Python expertise to deliver faster, scalable, and cost-efficient solutions for complex data problems. I help companies collect, structure, and transform data into usable formats for Machine Learning, analytics dashboards, and business automation. 🚀 Core Expertise 🤖 AI-Powered Web Scraping Intelligent scraping using LLMs + Python Dynamic websites, login systems, pagination, JS rendering Scrapy, Selenium, Playwright, Requests, BeautifulSoup Automatic data cleaning and structuring for AI usage 🧠 AI & LLM Automation GPT / Claude powered workflows AI agents for decision making pipelines prompt engineering & structured output pipelines automated classification & enrichment of datasets 📊 Data Engineering for ML Projects dataset preparation for ML models data normalization and transformation structured JSON, CSV, database pipelines large-scale scraping (millions of records) 📈 Dashboard & Web Apps for Data Projects dashboards for scraped or AI processed data FastAPI / Django APIs Next.js dashboards data visualization pipelines ⚙️ Automation Systems workflow automation using Python & APIs n8n, cron jobs, server automation PDF parsing, document extraction business process automation ☁️ Cloud & Infrastructure AWS deployment (EC2, S3, Lambda) proxy rotation, captcha solving scalable scraping architecture Docker based deployments 💡 Example Projects I Can Build AI-powered lead generation scraper ML training dataset collection pipelines automated competitor price monitoring document & PDF data extraction systems AI classification pipeline for companies or products dashboard showing real-time scraped insights automation bots for repetitive online tasks 🛠 Tech Stack Python • Scrapy • Selenium • Playwright • FastAPI • Django LLM APIs • OpenAI • Claude • Prompt Engineering Next.js • API Integration • PostgreSQL • MongoDB AWS • Docker • Proxy rotation • CAPTCHA solving AI Tools: Codex • Cursor • Copilot • Claude • ChatGPT ⭐ Why hire me? ✔ Combine 12 years scraping experience + modern AI tools ✔ faster development using AI-assisted coding ✔ scalable architecture for large datasets ✔ clear communication & reliable delivery ✔ long-term collaboration mindset If your project involves AI data collection, automation, or ML dataset preparation, I can help you build a reliable system quickly. 📩 Send me a message — I can suggest best architecture for your project.

I am a AI specialist and a problem-solver. I am expert in using Python to develop effective machine learning models. I have experience with AWS and Tensorflow and have built applications, models, and solutions for a variety of companies. I have developed cutting edge, custom machine learning models and successfully integrated them within existing structures. My goal is to revolutionize your business. I believe that machine learning and AI is the path forward, and I can help you obtain value from the data you collect. If you want to innovation and creativity in your business, reach out to me.

I am an AI Quality Assurance and Validation Specialist with a PhD-level scientific background and hands-on experience evaluating AI systems used in high-stakes, regulated, and technical environments. My work focuses on ensuring AI outputs are accurate, consistent, defensible, and aligned with real-world constraints, especially in domains where errors matter, such as science, healthcare, and compliance-driven systems. I regularly support teams with: AI model evaluation, benchmarking, and QA testing, Data annotation, labeling, and validation for training and evaluation, Instruction following and rubric-based assessment, Hallucination detection, edge-case analysis, and failure mode identification, Scientific and technical content review for accuracy and clarity I bring a rare hybrid skill set: deep scientific training combined with practical AI evaluation experience. I have worked with complex datasets, experimental protocols, and validation frameworks, and I apply that same rigor to AI systems. Clients work with me when they need: -High-quality, reliable AI evaluations (not superficial reviews) -Clear written feedback that engineers and researchers can act on -Someone who understands both technical nuance and real-world impact I am detail-oriented, fast, and communicative. I take ownership of quality and treat every project as if it will be audited later. If you need a QA partner who can think critically, spot subtle issues, and improve model performance through structured evaluation, I’m happy to help.

Experienced in python programming, data analysis and machine learning. UK-based and happy to have a quick chat on your projects!

I am a Python Data Scientist with a proven track record of turning complex datasets into clear, actionable insights. My expertise covers the full data pipeline—data entry, cleaning, preprocessing, and advanced analytics—ensuring accuracy and efficiency at every stage. I specialize in data visualization using Tableau and Power BI, creating dashboards that not only look polished but also tell meaningful stories that drive decision‑making. On the analytical side, I am skilled in regression modeling, hypothesis testing, and clustering techniques such as K‑means, helping clients uncover patterns, segment audiences, and forecast outcomes with confidence. My workflow emphasizes tidy, reproducible code and scalable solutions, so projects remain efficient and adaptable over time. Clients value my team‑oriented mindset, attention to detail, and commitment to delivering high‑quality results. I approach every project with curiosity, precision, and a willingness to learn, ensuring that the solutions I provide are both technically sound and tailored to your unique goals. If you’re looking for a data professional who can bridge the gap between raw numbers and clear business insights, I’d be glad to collaborate on your next project.

Hi, I'm an experienced mathematics writer, curriculum developer, and educator with over 5 years of teaching and content creation experience both online and in classrooms. I specialize in transforming complex math concepts into clear, engaging, and visually supported lessons for learners from elementary to college level. I create Common Core-aligned, age-appropriate, and visually enhanced math content using LaTeX, digital diagrams, and real-world examples. My writing and lesson designs are not only accurate but also pedagogically sound, built on my B.Ed background and a deep understanding of how students learn mathematics best. ✔️ Curriculum Development & Lesson Design: Common Core, IB, GCSE, and national curricula ✔️ Math Content Writing: Worksheets, quizzes, eBooks, explanations, and textbook chapters ✔️ LaTeX Formatting: Professionally written equations and math visuals ✔️ Interactive & Visual Learning Materials: Using Python, GeoGebra, and other digital tools ✔️ Custom Math Resources: Tailored to your students’ needs or platform requirements 📌Tools & Approach: • Visual design and content structuring using modern tools (Python, JavaScript, GeoGebra, Desmos, LaTeX, Canva, Microsoft office, EfofeX) • LMS-based learning environments • AI-assisted workflows for scalable and adaptive learning (Extensive knowledge of workplace automation, 8n8, LMS handling in education) • Storyboarding

Data Scientist with 8.5+ years of experience delivering AI, Machine Learning, NLP, and GenAI solutions across banking, fintech, retail, and marketing analytics. I specialize in building end-to-end predictive models, customer segmentation, experimentation frameworks, LLM applications, and scalable analytics platforms that drive measurable business impact. I've led high-impact projects at Synchrony Financial, dunnhumby, and Cognizant, including GenAI-powered intent classification, LLM citation prediction, sales forecasting, propensity modeling, causal inference, and marketing optimization. My expertise spans Python, SQL, PySpark, XGBoost, LLMs, NLP, Tableau, Power BI, AWS, and GCP. I focus on translating complex business problems into practical, data-driven solutions that improve decision-making, automate workflows, and deliver measurable ROI.