I am an Applied AI & Machine Learning Consultant with a strong background in data analytics, predictive modeling, statistical analysis, and decision support systems. My experience spans finance, lending, capital markets, marine analytics, retail, and business intelligence, where I have developed data-driven solutions that improve forecasting accuracy, automate analytical workflows, and support strategic decision-making. My core expertise lies in transforming raw data into actionable insights through data preparation, feature engineering, statistical modeling, machine learning, and interactive analytics. I enjoy working on challenging analytical problems, particularly those involving predictive modeling, time-series forecasting, risk assessment, and large-scale structured datasets. My focus is always on building practical, production-ready solutions rather than purely theoretical models. I have hands-on experience developing regression, classification, ensemble learning, and forecasting models using Python and R. My work includes model selection, hyperparameter optimization, feature engineering, model validation, explainability, performance monitoring, and deployment-ready analytics pipelines. I am comfortable working with algorithms such as XGBoost, LightGBM, CatBoost, Random Forest, Gradient Boosting, Logistic Regression, Elastic Net, Support Vector Machines, Neural Networks, and time-series techniques including ARIMA and GARCH, while selecting the most appropriate approach based on business objectives and data characteristics. My experience also includes financial and quantitative analytics, where I have built predictive models and analytical dashboards for mortgage-backed securities, probability of default, options analytics, stock market analysis, foreign exchange research, and market intelligence. These projects strengthened my understanding of financial datasets, feature engineering for market data, risk modeling, and the importance of robust validation techniques for real-world decision making. Beyond predictive modeling, I develop interactive analytical applications and dashboards using Streamlit and R Shiny, enabling stakeholders to visualize complex datasets, monitor model outputs, and interact with analytics through intuitive web-based interfaces. My technical toolkit includes Python (Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, PyTorch, SciPy, Statsmodels, Plotly, Streamlit, FastAPI), R (tidyverse, caret, glmnet, forecast, Shiny), SQL, Power BI, Tableau, Git, Jupyter Notebook, Google Colab, and cloud-based analytics environments. I also recently expanded my expertise into modern AI applications, prompt engineering, AI workflow automation, agentic AI, AI productivity systems, and practical enterprise adoption of Generative AI technologies. This complements my existing machine learning experience by helping organizations combine traditional predictive analytics with modern AI-powered workflows. I believe AI should be applied thoughtfully. I use classical statistical and machine learning methods when they provide the best predictive performance, and leverage Generative AI where it genuinely improves productivity, automation, knowledge extraction, or decision support. My approach emphasizes explainability, reproducibility, robust validation, and solutions that deliver measurable business value. Whether the objective is predictive analytics, statistical modeling, machine learning, AI-assisted automation, financial analytics, business intelligence, or interactive dashboards, I enjoy collaborating with clients to build scalable, reliable, and data-driven solutions that solve real business problems.

Turn raw web data into actionable business intelligence. I provide end-to-end data solutions, from building complex automated scrapers to performing deep statistical analysis. I don't just "get the data"—I clean, process, and analyze it so you can make informed decisions immediately. With a background in Python-driven automation and data science, I bridge the gap between technical data collection and strategic analysis. Phase 1: High-Fidelity Data Extraction I build custom, scalable scrapers that can handle modern web complexities: Dynamic Sites: Expert use of Playwright, Puppeteer, and Selenium for JavaScript-heavy applications. Speed & Scale: Utilizing BS4 and Scrapy for high-speed extraction from static sites. Anti-Bot Evasion: Bypassing Cloudflare, CAPTCHAs, and rate limits using advanced proxy rotation. Source Variety: Scraping E-commerce (Amazon/eBay), Lead Gen (LinkedIn/Google Maps), and Real Estate (Zillow). Phase 2: Professional Data Analysis Once the data is extracted, I use the Python data stack to extract its value: Data Cleaning: Deduplication, handling missing values, and formatting using Pandas and NumPy. Exploratory Analysis (EDA): Identifying trends, correlations, and outliers that impact your ROI. Visualization: Creating clear, professional reports to communicate findings. Database Management: Structuring and migrating your data into SQL, NoSQL, or Google Sheets. Why Choose My Services? Most freelancers offer either scraping or analysis. By hiring me, you eliminate the "middle man." You receive a finished product: a clean, validated dataset accompanied by a summary of what that data actually means for your business. I guarantee 100% data accuracy and maintainable, documented code for every project.

I am a data scientist and quantitative developer with more than 10 years of experience. I build, backtest, and automate trading strategies, and the work I take on is implementing an idea or a set of rules that you already have. I will be direct about what I do and do not do. I do not sell ready-made strategies, and I do not take work that depends on promising a profitable system. What I am good at is taking a defined edge, hypothesis, or rule set and turning it into something tested honestly and built to run unattended. You can get a first version from ChatGPT or Claude in an afternoon now, and that is genuinely useful. I use the same tools. The catch is that an AI will happily hand you a beautiful equity curve that quietly used future data, fit a hundred parameters to noise, and ignored slippage and fees, and then it falls apart the first week it trades live. Most of my value is knowing where those traps are: lookahead and data leakage, overfitting across many trials, survivorship bias, and the gap between a fill in a backtest and a fill in a thin order book. I test so the number you act on survives out of sample and in real execution, not only on paper. A few things I have built. Futures trading and market data analysis in Python. Trading systems in MetaTrader. Backtesting and optimization for a defined options strategy on SPX. A sentiment-driven ARIMAX forecaster for the S&P 500 that collects its own data. How I work on a strategy. Backtesting with realistic costs, slippage, and execution assumptions, walk-forward and out-of-sample testing, and an honest read on whether an edge is real or only fit the past. Implementation and automation across broker and exchange APIs, with the monitoring to run it unattended. And the statistics underneath, so position sizing and risk hold up. I have a PhD, which mostly shows up as a habit of asking whether a result is real before trusting it. I am Top Rated on Upwork with over 4,000 hours across 60-plus projects. If you have a strategy or an idea you want built and tested properly, or an AI-generated prototype you want pressure-tested before you risk money on it, tell me the rules and what you have, and I will give you a straight read. Stack: Python, Pandas, NumPy, backtesting frameworks, statsmodels, scikit-learn, MetaTrader (MQL), broker and market data APIs, SQL, Docker, AWS/GCP/Azure.

🎯 Transforming raw data into actionable insights with 1000+ hours of freelance experience. ✅ Recent project highlights: - Developed real-time sales dashboard for e-commerce client (40% faster decision-making) - Built healthcare KPI tracking system monitoring 15+ metrics in PowerBI - Automated financial reporting process (saved 20 hours weekly) 💡 How I can help your business: - Transform complex data into clear, interactive visualizations - Build automated reporting systems that save time and reduce errors - Optimize your ETL processes for better data quality - Create executive dashboards that drive strategic decisions 🛠️ Technical expertise: - BI Tools: PowerBI (Expert), Tableau, MS Excel - Programming: Python (Pandas, NumPy), SQL - Databases: MySQL, PostgreSQL, MS SQL Server - Specialties: Dashboard Development, ETL, Data Modeling, KPI Design 📊 Industry experience: Healthcare, E-commerce, Finance, Manufacturing ⭐ Client feedback: "Muhammet's analytical approach and attention to detail exceeded our expectations. He delivered a dashboard that transformed how we view our business data." 🚀 Why work with me: - Fast response time (under 1 hour) - Clear communication and regular updates - Delivery on time, every time - Post-project support included 💬 Let's discuss your data challenges - I provide free consultation and project scoping. ```

[NEW] You can talk-to-my-work using the link in the portfolio section! Are you looking for a Python expert to build cutting-edge trading systems, optimize financial data workflows, or develop scalable APIs? With 3+ years of experience in full-stack development and 50 successful freelance projects generating $150k, I specialize in delivering high-performance solutions for hedge funds, retail traders, and FinTech startups. 𝗪𝗵𝗮𝘁 𝗜 𝗢𝗳𝗳𝗲𝗿: Algorithmic Trading Systems: Custom strategies with IBKR, Binance, and CCXT integrations. Financial Data Analytics: Forecasting (ARIMA, SARIMA), NLP-based news analysis, and portfolio optimization. Scalable Backend Systems: APIs and serverless architectures using FastAPI, Flask, and AWS. Cloud Computing: Deployment, CI/CD workflows, and database integration with AWS tools. 𝗧𝗲𝗰𝗵 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 Languages: Python (Flask, Django, FastAPI), Advanced Data Structures. Tools: Redis, Celery, PostgreSQL, AWS (Lambda, API Gateway, DynamoDB). Data Science: Pandas, NumPy, scikit-learn, and geospatial analysis (GeoPandas). 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 & 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀: Certified AWS Machine Learning Specialist – Expertise in scalable AI/ML systems for finance. Upwork Skill Certification: Python Development & Back-End Development – Verified proficiency. AI/ML Quantitative Developer (QuantPy) – Advanced application of AI in quantitative finance. 𝗪𝗵𝘆 𝗪𝗼𝗿𝗸 𝗪𝗶𝘁𝗵 𝗠𝗲? I tailor solutions to your unique business needs, ensuring quality and scalability. I’m a strong communicator who delivers on time, every time. I’m committed to long-term collaborations and helping your business grow. Let’s create impactful solutions together! Message me today, and I’ll be happy to discuss your project.

Hi, I’m Alexander, a dedicated web scraping and data extraction specialist with 6+ years of experience helping businesses unlock insights from complex websites and APIs. Using Selenium, Scrapy, BeautifulSoup, and Playwright, I deliver custom web crawlers and automation solutions that save time, reduce costs, and drive smarter decisions. From e-commerce price monitoring to public/private search engines or databases, I make data work for you. Why Choose Me? Proven Results: - Scraped 50K+ product listings for an e-commerce client, optimizing pricing strategy by 30%. - Automated lead extraction for a marketing firm, saving 40 hours/week. - Advanced Expertise: Build robust web scrapers that handle anti-bot systems, proxies, and CAPTCHAs for sites like Amazon, eBay, or Twitter/X. - End-to-End Solutions: Deliver clean, structured data (CSV, JSON, SQL, Excel) integrated into your systems—Google Sheets, Airtable, or custom dashboards. - Automation Mastery: Design Python-based workflows with selenium, requests, or asyncio to eliminate manual tasks and scale operations. - Ethical & Compliant: All scraping can be implemented to adheres to robots.txt, GDPR, and CCPA, ensuring legal and sustainable data collection. What I Offer ✅ Web Scraping & Crawling: Custom scrapers for dynamic/static sites, APIs, and databases (e.g., LinkedIn, Shopify, real estate platforms). ✅ Data Extraction & Processing: Extract, clean, and transform data from PDFs, HTML, or APIs into usable formats. ✅ Automation Pipelines: Scheduled scrapers and bots deployed on AWS, GCP, or Docker for 99.9% uptime. ✅ Specialized Use Cases: E-commerce, finance, travel, social media, and competitor analysis. Tech Stack ✔ Web Scraping: Selenium, Scrapy, BeautifulSoup, Playwright, Requests ✔ Data Processing: Pandas, NumPy, regex, Tesseract OCR ✔ Automation: Python, asyncio, task schedulers, Excel/Google Sheets integration ✔ APIs & Cloud: REST APIs, AWS, GCP, proxy rotation, headless browsers Ready to harness web data? Message me for a free 15-minute consultation or view my GitHub for sample web scraping projects. Let’s automate your data and boost your growth! Skills: Web Scraping, Data Extraction, Selenium, Python, Scrapy, BeautifulSoup, Web Crawling, Data Mining, API Integration, Automation (5.0/5 ★★★★★ | 60+ Jobs Completed | Top 1% Upwork Talent)

I'm a Data Scientist and Machine Learning Engineer with 5+ years of experience helping SMEs turn messy data, unstructured text, and manual workflows into intelligent, automated systems that drive real business outcomes. My core strength lies in building production-ready ML and NLP solutions, from custom LLM applications and RAG pipelines to fully autonomous AI agents, that don't just work in a notebook but actually perform at scale. I've worked across healthcare, fintech, e-commerce, SaaS, and customer support, and I bring both the technical depth and business thinking to every project. You're probably sitting on thousands of support tickets, internal documents, customer conversations, or operational data that your team processes manually. Leads slip through the cracks, customers wait too long for answers, insights stay buried in spreadsheets, and your competitors are already automating what your team still does by hand. The longer you wait, the more it costs you in time, in errors, and in missed opportunities. 𝐌𝐲 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐔𝐦𝐛𝐫𝐞𝐥𝐥𝐚: 1. LLMs & Generative AI: OpenAI API (GPT-4, GPT-3.5), Claude, Gemini API, LangChain, LlamaIndex, RAG Pipelines, Prompt Engineering, Zero-shot & Few-shot Reasoning, In-context Learning, Text-to-SQL 2. Agentic AI: Multi-agent systems, LangGraph, CrewAI, AutoGen, Tool-use & Function Calling, Autonomous Workflow Agents, Memory & Planning Architectures 3. NLP: Named Entity Recognition, Text Classification, Sentiment Analysis, Semantic Search, Vector Embeddings (OpenAI, Sentence-Transformers), Topic Modeling, Summarization, Wav2Vec2.0, Whisper, HuBERT 4. Machine Learning & Deep Learning: CNN, LSTM, Transformer-based Models, Diffusion Models, LoRA/QLoRA Fine-tuning, Ensemble Modeling, Scikit-learn, XGBoost, PyTorch, TensorFlow 5. Data Science & Analytics: Exploratory Data Analysis, Statistical Modeling, A/B Testing, Forecasting, Pandas, NumPy, SQL, Tableau, Power BI 6. MLOps & Deployment: FastAPI, Flask, Streamlit, AWS (Bedrock, EC2, Lambda), CI/CD Pipelines, Apache Airflow, n8n, PostgreSQL, Vector Databases (Pinecone, Weaviate, ChromaDB) I design and deploy AI systems that automate customer support with 90%+ resolution accuracy, build RAG-powered knowledge assistants that cut research time by 10x, deploy autonomous agents that handle multi-step workflows end to end, and turn raw business data into predictive models that drive smarter decisions. My clients don't hire me for the tech. They hire me for the results. That means fewer manual errors, 60 to 80% faster processing, reduced operational costs, and decision-making backed by real-time intelligence. Whether it's an AI agent saving $50K/year in support overhead or an NLP pipeline that replaces 3 full-time analysts, I build solutions where the ROI is obvious within weeks, not months. Every engagement starts with a 𝐅𝐑𝐄𝐄 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐭𝐢𝐨𝐧 where I assess your data challenge, identify quick wins, and map out a clear roadmap. I deliver production-grade systems with clean documentation, so your team isn't dependent on me forever. 𝗦𝗲𝗻𝗱 𝗮 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝗼𝗿 𝗶𝗻𝘃𝗶𝘁𝗲 𝗺𝗲 𝘁𝗼 𝘆𝗼𝘂𝗿 𝗷𝗼𝗯, 𝗰𝗼𝘀𝘁𝘀 𝘆𝗼𝘂 𝗮𝗯𝘀𝗼𝗹𝘂𝘁𝗲𝗹𝘆 𝗻𝗼𝘁𝗵𝗶𝗻𝗴, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝘄𝗼𝗿𝘀𝘁 𝘁𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝗶𝘀 𝘆𝗼𝘂 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝘄𝗵𝗼 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗴𝗲𝘁𝘀 𝘆𝗼𝘂𝗿 𝘃𝗶𝘀𝗶𝗼𝗻. Thanks Aneeba A.

I am a 7-year experienced data scientist with a strong background in machine learning, statistical modeling, and data analysis. I have a proven track record of designing and implementing data-driven solutions for a wide range of applications, from predictive modeling and natural language processing to computer vision and anomaly detection. Some of my key strengths and skills include: 6+ years of experience in (Machine Learning, NLP, Big Data, API, and Back-End Development). Built end-to-end machine learning systems using Natural Language Processing and MLOps. ✅ Successfully Completed Projects: Text Classification We develop custom text classification solutions using advanced NLP techniques tailored to your specific business requirements. Leveraging Python, Pytorch, and Hugging Face transformers, we enable precise data categorization across applications such as intent detection, document categorization, and sentiment analysis, enhancing your decision-making processes and operational efficiency. Chatbots We specialize in creating custom chatbots that integrate seamlessly with your business environment. Using semantic search and large language models, our chatbots deliver accurate, context-aware responses, and can interface with both internal and external APIs. A tailored dashboard allows for continuous monitoring and updating, ensuring the chatbot evolves with your business needs. Automating Support Tickets We offer bespoke solutions for automating support ticket management, employing NLP to analyze, categorize, and prioritize inquiries effectively. Our customized systems enhance response efficiency and accuracy, improving overall customer satisfaction while reducing response times. NL2SQL Our NL2SQL services transform how you interact with your databases. By customizing solutions that allow natural language querying, we make data access straightforward and intuitive, complete with visualizations to aid in understanding complex datasets. Speech to Text We provide customized speech to text services, employing cutting-edge speech recognition technologies to cater to specific client needs. Ideal for creating efficient documentation and enabling voice-driven commands, this solution boosts productivity and accessibility. Text to Speech We offer custom text to speech conversions to enhance user engagement across digital platforms. Tailored to your specific content needs, our solutions make your digital content accessible and interactive with natural-sounding speech. Product Description Generation Generate unique and engaging product descriptions with our AI-driven solutions that combine textual and visual data. Tailored to your specific e-commerce needs, our service ensures SEO-friendly descriptions that captivate your audience. AI Chrome Extension Development Develop bespoke AI-powered Chrome extensions. These are not off-the-shelf solutions; they are crafted to enhance your specific browser functionality, improving productivity and user experience with smart features. OCR Document Parsing Customize your document parsing processes with our OCR technology. We design solutions that cater to your specific document types, such as invoices and resumes, automating data extraction and minimizing errors. Fine-tuning Open Source LLMs We provide custom services to fine-tune open-source large language models to your unique operational needs, ensuring that your AI solutions are perfectly aligned with your business tasks. Personal Assistant or Agent I build complex, customized personal assistant applications using LangChain and crewAI. These applications are designed to provide stateful, multi-actor AI interactions tailored to enhance your organizational processes and user experiences. 🧰 My technic Skills: Languages: Python, TypeScript, SQL. ML Libraries: Pandas, Scikit learn, Spacy, Tensorflow, , Pytorch, Transformers Machine Learning (Classification, Regression, clustering, Decision Trees, K-Means Clustering, hierarchical clustering), Deep Learning (DNN, CNN, RNN, Transfer learning, AlexNet, LeNet, VGG, Resnet, Inception, MobileNet, YOLO, Transpose CNN, U-Net, LSTM, LLM, GenAI, RAG), Statistical Methods (Predictive analysis, Hypothesis Testing and Confidence Intervals, Principal Component Analysis, LDA and Dimensionality Reduction), Programming Languages and tools (Python, Java, HTML and CSS, TypeScript, Tailwindcss, Nextjs), Version Control Tools (Git), Python Libraries (Sklearn, Scipy, Statsmodel, Pandas, NumPy, Seaborn, Matplotlib, Selenium, BS4, NLTK, TensorFlow, Keras, shap, Boto3, Flask, FastAPI, Streamlit, langchain, langfuse, langsmith, llama-index), Scripting Language (Unix), Database Language (SQL), Data Reporting Tool (Excel, GCP Data Studio), Cloud Tools (AWS (Bedrock, lambda, RDS, EC2, sagemaker, s3, Lex), GCP (Bigquery, Dataproc, Dataflow, Vertex AI, cloud SQL, etc.))

Hi! I'm a Data Engineer and Data Scientist with over 3 years of experience building scalable data pipelines, cleaning and analyzing complex datasets, and delivering AI/ML solutions that create real business value. I specialize in designing event-driven cloud architectures, developing ETL/ELT pipelines for real-time and batch processing. Whether it's processing terabytes of data or fine-tuning a neural network — I’m all about clean code, solid logic, and measurable impact.

🚀 Hello! I’m Abdelmalik, Quant Trader & Quantitative Researcher, building production-grade buy-side trading and pricing systems, from signal generation to live execution under real-market constraints. I design end-to-end quantitative engines that operate reliably with noisy or delayed data, microstructure effects, latency budgets, and strict forward-only decision rules. My work is desk-oriented: models are judged on robustness, execution quality, regime stability, and deployability. I work with clear milestones, written acceptance criteria, reproducible deliverables, and transparent communication so that scope, validation results, and payment expectations are aligned before each project phase begins. 📈 Quant Trading, Research & Derivatives Systematic Trading & Execution. Live strategies with microstructure-aware gating: spread in basis points, aggressor ratio, upticks. Regime-adaptive logic across trend, volatility and liquidity. Risk-based sizing using ATR, staged exits and VWAP-aware liquidation. Broker OCO orders, circuit breakers and idempotent execution to prevent double fills. Deterministic replays and ghost A/B tests before production. 📊 Options & Exotic Pricing Pricing engines in C++ and Python using Black–Scholes, Heston, Dupire and Variance Gamma. Exotic structures including barriers and baskets. Numerical methods based on correlated and variance-reduced Monte Carlo, and PDEs using Crank–Nicolson with Rannacher smoothing. Volatility surfaces, smile reconstruction, robust proxy aggregation, walk-forward debiasing, affine scale correction and panel volatility guards. 📉 Validation & Results Strict walk-forward validation and multi-regime stress tests. R² between 0.83 and 0.92 on sector basket option pricers. RMSE below 1 basis point on barrier pricing grids. Sub-second C++ kernels with deterministic and replayable outputs. Stable pricing using 15-minute delayed options data. 🧠 Machine Learning Production Models built with Sklearn, XGBoost, PyTorch and TensorFlow. Probabilistic calibration using Platt scaling and isotonic regression, with Brier score and ECE monitoring. Drift detection using PSI, class-imbalance handling and robust cross-validation. GPU acceleration with CUDA and CuPy. Deployment via FastAPI and Streamlit. ⚙️ Quant Infrastructure High-performance C++17 cores using OpenMP, AVX and PyBind11, with parallel Monte Carlo and Cholesky correlation. Market data pipelines using Polygon with minute-level options and level 2 data. Production observability with Prometheus and Grafana SLOs, Redis-based event architecture, atomic snapshots and audit-safe logs. 🎓 Training: Columbia, Yale, Stanford, Wharton, NYIF 🌍 Availability: Remote worldwide or on-site Casablanca 🤝 Open to buy-side quant trading, systematic execution and advanced pricing or risk teams