🔍 Are you losing revenue to hidden churn, slow reports, or broken data pipelines? I'm Shariful — a Python Data Scientist specializing in Machine Learning, ETL Automation, and Predictive Analytics. I turn raw, messy data into decisions that directly grow your revenue. ━━━━━━━━━━━━━━━━━━━━━ 💼 WHAT I DELIVER (REAL RESULTS): ━━━━━━━━━━━━━━━━━━━━━ ✅ Churn Prediction Model → 90% accuracy, retained in annual revenue. ✅ Recommendation Engine (Scikit-Learn) → boosted Average Order Value by 28%. ✅ Automated ETL Pipeline → saved a marketing agency 20+ hours/week. ✅ Sports Results Extraction (PDF → JSON) → delivered error-free structured data with QA validation. ✅ Stock Movement Forecasting → ML model for election-period market prediction. ━━━━━━━━━━━━━━━━━━━━━ 🛠 SERVICES I OFFER: ━━━━━━━━━━━━━━━━━━━━━ → Machine Learning Models (Classification, Regression, Forecasting, Clustering). → ETL Pipeline Development (PDF, API, Web Scraping → JSON/SQL/CSV). → Python Automation (Replace manual workflows with scripts that run 24/7). → Business Intelligence Dashboards (Tableau, Plotly/Dash). → Exploratory & Predictive Data Analysis. → Time Series Forecasting & Anomaly Detection. ━━━━━━━━━━━━━━━━━━━━━ ⚙️ TECH STACK: ━━━━━━━━━━━━━━━━━━━━━ Python · Pandas · NumPy · Scikit-Learn · TensorFlow SQL · Tableau · Plotly/Dash REST APIs · Web Scraping · Cron Jobs · ETL Pipelines ━━━━━━━━━━━━━━━━━━━━━ 🏆 WHY CLIENTS CHOOSE ME: ━━━━━━━━━━━━━━━━━━━━━ ⭐ 100% Job Success Score. ⚡ 4–8 hr avg. response time. 📦 Deliver ahead of schedule — every time. 💬 "Clear communicator. Proactive updates. Business-focused mindset." — Verified Client. I don't just build models. I build systems that make your business smarter. 📩 Send me your project details — I'll reply within a few hours with a clear action plan.

I have spent 8 years at the intersection of data, AI, and the question nobody wants to ask “does it actually deliver results?” From forecasting systems to LLM pipelines and autonomous agents built for real world problems where off-the-shelf solutions fail. The tools change with every project. The bar doesn't. Here is an overview of my Stack 𝗠𝗟 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀: PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, CatBoost, statsmodels 𝗟𝗟𝗠𝘀 & 𝗡𝗟𝗣: Open AI, Claude, Gemini, Grok, LLaMA, Mistral, DeepSeek, BERT, BART, SetFit, HuggingFace 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 & 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: LangChain, LangGraph, RAG Pipelines, n8n, Make, OpenAI API, Anthropic API, Lovable, OpenClaw 𝗩𝗲𝗰𝘁𝗼𝗿 & 𝗦𝗲𝗮𝗿𝗰𝗵: Pinecone, FAISS, ChromaDB, SentenceTransformers, Embeddings 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: pandas, NumPy, Parquet, Airflow, dbt, ETL Pipelines 𝗔𝗣𝗜𝘀 & 𝗦𝗰𝗿𝗮𝗽𝗶𝗻𝗴: FastAPI, Flask, WebSocket, PRAW, BeautifulSoup, Selenium 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Matplotlib, Seaborn, Plotly, Tableau, PowerBI, SHAP 𝗖𝗹𝗼𝘂𝗱 & 𝗜𝗻𝗳𝗿𝗮: AWS EC2, SageMaker, AWS Bedrock, Firebase, Docker, VPS 𝗙𝗿𝗼𝗻𝘁𝗲𝗻𝗱 & 𝗔𝗽𝗽𝘀: React, Next.js, Streamlit, Gradio, Lovable 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Gmail API, Google Calendar API, WhatsApp API, Stripe, PayPal, Odoo You can get a feel for the work pretty quickly. Here's a slice. → 𝗔𝗜 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 • Built a 𝒇𝒖𝒍𝒍-𝒄𝒚𝒄𝒍𝒆 𝑨𝑰 𝒉𝒊𝒓𝒊𝒏𝒈 𝒑𝒊𝒑𝒆𝒍𝒊𝒏𝒆 using n8n to orchestrate OpenAI-powered resume parsing with Gmail, Google Sheets, and Calendar APIs reducing 𝐻𝑅 𝑚𝑎𝑛𝑢𝑎𝑙 𝑤𝑜𝑟𝑘𝑙𝑜𝑎𝑑 𝑏𝑦 80% with centralized candidate tracking and automated scheduling. • Developed 𝒂 𝒓𝒆𝒂𝒍-𝒕𝒊𝒎𝒆 𝑨𝑰 𝒗𝒐𝒊𝒄𝒆 𝒂𝒈𝒆𝒏𝒕 supporting voice-to-voice, speech-to-text and text-to-text conversations via FastAPI and WebSocket with ultra low latency using GPT for dialogue management. • Built an 𝑨𝑰 𝒑𝒐𝒘𝒆𝒓𝒆𝒅 𝒕𝒆𝒍𝒆𝒎𝒆𝒅𝒊𝒄𝒊𝒏𝒆 𝒑𝒍𝒂𝒕𝒇𝒐𝒓𝒎 on Next.js and Firebase with role-based AI prompts, automated symptom collection and 𝑟𝑒𝑎𝑙 𝑡𝑖𝑚𝑒 𝑐𝑙𝑖𝑛𝑖𝑐𝑎𝑙 𝑖𝑛𝑠𝑖𝑔ℎ𝑡𝑠 for patient doctor interaction. → 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 & 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 From pharmaceutical supply chains to crypto markets, I build forecasting systems that drive real inventory, budget and trading decisions. • Built a 3𝑴+ 𝒓𝒆𝒄𝒐𝒓𝒅 𝒑𝒉𝒂𝒓𝒎𝒂 𝒇𝒐𝒓𝒆𝒄𝒂𝒔𝒕𝒊𝒏𝒈 𝒔𝒚𝒔𝒕𝒆𝒎 pipeline: XGBoost R²=0.90, 20% accuracy gain, 17-chart EDA uncovering SKU concentration risk and billing-cycle demand patterns • 𝑪𝒓𝒄𝒓𝒚𝒑𝒕𝒐 𝒇𝒐𝒓𝒆𝒄𝒂𝒔𝒕𝒊𝒏𝒈 𝒎𝒐𝒅𝒆𝒍𝒔 using ARIMA + Reddit sentiment (PRAW + SetFit) → BUY/SELL/HOLD signals for BTC, ETH, SOL, DOGE • 𝑫𝒆𝒎𝒂𝒏𝒅 𝒇𝒐𝒓𝒆𝒄𝒂𝒔𝒕𝒊𝒏𝒈 𝒑𝒊𝒑𝒆𝒍𝒊𝒏𝒆 (LR, XGBoost, RF, LSTM) achieving R²~0.99 used car price prediction deployed via Flask → 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 I build classification, regression, and validation systems with rigorous evaluation not just accuracy scores but defensible, 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏-𝒓𝒆𝒂𝒅𝒚 𝒎𝒐𝒅𝒆𝒍𝒔. • SVM, Gradient Boosting, MLP, XGBoost, Logistic Regression always with GridSearch and KFold CV for hyperparameter integrity • Diabetes detection: 86% accuracy on 3-class imbalanced clinical dataset with feature engineering and undersampling experiments → 𝗡𝗟𝗣 & 𝗟𝗟𝗠-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 I combine classical text modeling with modern LLMs to extract structured insight from unstructured data at scale. • Claude 3.5 Sonnet (AWS Bedrock) + BART MNLI + SentenceTransformer pipeline quantifying open ended survey sentiment for fragrance product strategy • Real-time Reddit 𝒔𝒆𝒏𝒕𝒊𝒎𝒆𝒏𝒕 𝒅𝒂𝒔𝒉𝒃𝒐𝒂𝒓𝒅 for ASTS ticker upvote-weighted transformer scoring with daily trend visualization • 𝑻𝒆𝒙𝒕 𝑪𝒍𝒂𝒔𝒔𝒊𝒇𝒊𝒆𝒓 across disaster tweets (TFIDF, 80%), IMDB reviews (LSTM, 86%) and news categorization (CNN + GloVe, 75%) • GPT-4o, Claude, LLaMA, Grok and Mistral used as deliberate data enrichment and annotation tools inside ML pipelines → MLOps & Production Deployment: • Model training, validation, and deployment pipelines • Docker containerization and cloud deployment (AWS, GCP) • Model monitoring, versioning, and automated retraining • FastAPI and Flask-based ML serving infrastructure → Cloud & DevOps: • AWS deployment and infrastructure management • Docker containerization and Kubernetes orchestration • CI/CD pipeline setup and automation • Performance monitoring and scaling I work with startups building their first AI product, enterprises with complex data problems, and individuals with unique challenges nobody else wants to touch. If the problem is hard and the data is messy that's exactly where I do my best work. Send me a message and let's figure out if I'm the right fit. I will tell you within 24 hours whether I can help and how.

I’m a results driven Data Analyst with hands on experience in building end to end data solutions from data extraction and transformation to insightful visualization and reporting. I specialize in designing scalable ETL pipelines using BigQuery and Python, ensuring clean, reliable, and analysis ready data for decision making. On the data engineering side, I work extensively with ETL processes, extracting data from multiple sources such as APIs, databases, and marketing platforms, transforming it using SQL and Python, and loading it into data warehouses like BigQuery. I also work with tools like Airbyte for seamless data integration and Apache Airflow for workflow orchestration, scheduling, and automation of data pipelines. I focus on optimizing query performance, automating workflows, and maintaining high data accuracy. Analytics and Reporting Expertise: -Looker for advanced data modeling and scalable BI solutions -Looker Studio for interactive and client friendly dashboards -Power BI for business reporting and deep data visualization -Swydo for marketing performance reporting and client reporting automation -Databox for real time KPI tracking and business dashboards -Google Sheets and Excel for quick analysis and lightweight reporting -Other visualization and reporting tools as per business requirements I also bring strong expertise in tracking and analytics implementation. I have worked extensively with GA4, Google Tag Manager GTM, and Mixpanel, setting up event tracking, conversion tracking, funnels, user journey analysis, and debugging tracking issues to ensure accurate and reliable data collection. In Mixpanel, I help businesses with product analytics, event design, funnel optimization, retention analysis, and actionable user insights. Additionally, I work with various Looker Studio connectors including Supermetrics, BigQuery native connectors, and other third party integrations to unify data from platforms like Google Ads, Facebook Ads, Shopify, and CRM systems. I also have experience working with paid Looker Looker BI, including LookML modeling, building scalable data models, and creating enterprise level dashboards. I have worked with multiple clients across the US and UK, delivering data solutions tailored to different business needs, marketing strategies, and reporting requirements. What I can help you with: -End to end ETL pipeline development -BigQuery data warehousing and optimization -Data integration using Airbyte and API based pipelines -Workflow orchestration using Apache Airflow -Dashboard creation using Looker, Looker Studio, and Power BI -GA4, GTM, and Mixpanel tracking setup and audits Product and marketing analytics -Data integration using connectors like Supermetrics and APIs -Advanced reporting and business insights -I focus on delivering clear, actionable insights that help businesses grow and make smarter decisions.

I'm an AI Engineer and NLP Developer with a strong focus on building intelligent systems using cutting-edge technologies in Natural Language Processing, Generative AI, and Full Stack Development. My expertise includes working with LLMs, embedding models (like OpenAI embeddings, BERT, S-BERT), and clustering algorithms (such as BERT-Topic) to extract insights and build semantic understanding into applications. I specialize in topic modeling, dimensionality reduction, and adaptive clustering for scalable data analysis. I have hands-on experience deploying AI solutions on GPU-based infrastructure using RunPod and building state-driven conversational agents using LangGraph, FastAPI, and WebSocket for real-time interactions. I frequently use tools like Gradio to create intuitive user interfaces for AI-powered applications. On the development side, I work with modern web stacks, including ReactJS, NextJS, NodeJS, and MongoDB, and have implemented semantic search systems using vector databases and sentence transformers. I'm also well-versed in machine learning, deep learning, and data visualization using Python libraries such as Pandas, NumPy, scikit-learn, TensorFlow, Keras, Matplotlib, and Seaborn. With a solid foundation in data structures, algorithms, and multiple programming languages (Python, JavaScript, Java, C++, Kotlin), I bring both depth and flexibility to AI-driven problem solving.

Before you put real capital behind a strategy, you want someone whose job is to try to break it. I build and audit backtests that account for what quietly kills live performance: look-ahead bias, survivorship, optimistic fills, fee drag, and overfit parameters. What I do: • Backtest & Strategy Validation: Rules-based strategies across equities, options, futures, and crypto. I'll test any market except prediction markets. You get a reproducible codebase, a written assumptions document, and diagnostics that tell you whether the edge is real: walk-forward analysis, in-sample / out-of-sample results, scenario / regime stress tests and parameter-stability checks. • Backtest & Platform Audits: A second opinion before you launch your platform, scale capital into a strategy or trust a backtesting tool. I look for the bugs and biases that inflate results or mislead users, and I document each one with its measured impact on the numbers. • Hedging & Risk Overlays: Delta hedges, band/regime-based hedging policies, funding/carry modeling, and PnL decomposition. How much of your results comes from edge vs. fees vs. hedge vs. carry vs. costs? • From Validated to Live: A strategy that survives testing shouldn't stay in a notebook. I build the path to automation: point-in-time-correct datasets, broker and data-vendor API integrations, and scheduled jobs with executions tested live. The result: a validated strategy moved from research into a running, monitored system. Most engagements start with a small fixed-scope pilot: a single, defined deliverable at a fixed price, so you can judge the work before committing your capital or deciding to dive deeper. Your strategy and IP stay yours; I'm comfortable signing an NDA before you share anything. If your strategy doesn't survive honest testing, I'll show you exactly where it breaks and why. It's better to learn in testing than to discover it with live capital. My Background Since 2018 I've built and validated trading systems for small funds, prop traders, and private traders. Along the way I co-founded ComhlaTech, a predictive-analytics trading strategy company, where I advised on strategy and risk. I trade my own capital and have passed funded-trader evaluations at FTMO and Topstep. Tools & Skills Backtesting • Python • Pandas • NumPy • Time-Series Data • ETL • SQL • API Integration • Automation • Statistical Analysis

I am a highly skilled data analyst with expertise in a variety of powerful tools and technologies, including: ✅Python: Experienced in using libraries like Pandas, NumPy, scikit-learn and TensorFlow ✅ Selenium: Proficient in web scraping to automate data extraction from websites. ✅Tableau: Proficient in Tableau, a powerful data visualization tool that allows for intuitive ✅SQL: Proficient in extracting and manipulating data from relational databases. ✅SAS: Well-versed in employing SAS for advanced analytics, statistical modeling. ✅R: Skilled in utilizing R packages for statistical analysis and data visualization. With these tools at my disposal, I excel in analyzing large datasets, identifying trends, patterns, and correlations, and providing data-driven insights and recommendations.

I am a Senior Data Engineer & Data Analyst with over 7 years of hands-on experience across SQL Databases, Data Engineering, ETL Pipelines, Cloud environments, Data Analytics and Data Warehousing. I deliver end-to-end data solutions, seamlessly bridging the gap between backend ETL Pipelines and frontend business insights to help companies make faster, better decisions. WHAT CAN I DO FOR YOU: • Build ETL and ELT pipelines to centralize fragmented business data. • Design data warehouses and dimensional models (star and snowflake). • Optimize complex SQL queries and improve database performance using standard data optimization techniques. • Develop interactive, automated dashboards and reporting suites for business stakeholders using Power BI, MicroStrategy, Superset, and Qlik. • Implement cloud data solutions using the Microsoft Azure ecosystem (Data Factory, Synapse, Fabric, Data Lake). • Clean, structure, format, and prepare massive, messy datasets for deep data analytics. TECHNICAL STACK: • Cloud & Warehouses: Azure (Data Factory, Synapse, Fabric, Azure SQL, ADLS), Snowflake, Teradata. • ETL Tools: Azure Data Factory, Talend Open Studio, Pentaho, Informatica, dbt, Apache NiFi. • BI & Analytics: Power BI, MicroStrategy, Apache Superset, Qlik, Looker Studio, Power Query. • Databases: PostgreSQL, MySQL, SQL Server, Oracle, Teradata, MongoDB, Cassandra. • Languages: SQL (T-SQL, PL/SQL), Python (Pandas, NumPy), PySpark. • Modeling: Data Modeling (ERD, Star Schema, Snowflake Schema). WHY CLIENTS HIRE ME: • 30+ successful data projects completed across engineering and analytics domains. • Strict focus on performance, long-term scalability, and clean, debt-free data architecture. • Clear, transparent communication and reliable, on-time delivery. • True end-to-end data expertise, tracking your data lifecycle from raw pipeline to final insight. If you need a reliable specialist who can streamline your data pipelines and turn raw tables into clear business insights, let’s talk. Click the "Invite to Job" or "Message" button to discuss your project goals.

I am a senior software engineer with a Master's in Computer Engineering from the University of Waterloo and several years of experience building production systems for companies including Huawei, Sumo Logic, and Rakuten. I help businesses build reliable web applications, scalable backend systems, cloud infrastructure, and AI powered automation tools. My work covers the full development cycle, from architecture and database design to API development, frontend implementation, deployment, and long term maintenance. What I can build for you: Full Stack Web Applications Modern web apps using React, TypeScript, Node.js, Python, Go, PostgreSQL, MongoDB, and cloud based deployment. AI Agents and LLM Integrations Custom AI assistants, RAG pipelines, OpenAI and Anthropic API integrations, prompt workflows, document automation, and AI features inside existing products. Workflow and Business Automation Automation for repetitive business tasks, internal tools, data workflows, SaaS integrations, scraping, scheduled jobs, reporting, and AI assisted operations. Backend and API Development REST APIs, GraphQL APIs, authentication, role based access, database design, microservices, background jobs, and performance optimization. Cloud Infrastructure and DevOps AWS, GCP, Docker, Kubernetes, CI/CD pipelines, server setup, monitoring, deployment automation, and Infrastructure as Code. High Performance Engineering Performance critical services, distributed systems, and backend components using Go, Rust, C, and C++ when speed and reliability matter. Core technologies: Python, TypeScript, JavaScript, Go, Rust, C/C++, SQL React, Node.js, FastAPI, Django, REST, GraphQL PostgreSQL, MySQL, MongoDB, Redis OpenAI API, Anthropic API, RAG, AI agents, LLM workflows AWS, GCP, Docker, Kubernetes, Terraform, GitHub Actions Why clients work with me: I write clean, maintainable, production ready code I communicate clearly and give regular progress updates I can own a project end to end or join an existing engineering team I focus on solving the business problem, not just writing code I care about reliability, scalability, and long term maintainability Whether you need an MVP, backend system, AI automation tool, cloud deployment, or a full product build, I can help you design it properly and ship it with confidence. Send me a message and I will be happy to discuss your project.

💻 Hi there! I am a Full-Stack Data Engineer, Data Scientist, and AI Integration Specialist with 3+ years of hands-on experience building end-to-end data solutions, intelligent automation systems, scalable web applications, and real-time machine learning products. My journey began in data extraction and web scraping, where I developed advanced scraping systems for e-commerce platforms, business intelligence, market research, and large-scale data collection. Over time, I expanded into full-stack data engineering, cloud deployment, AI integration, and production-grade application development, helping businesses transform raw data into live, intelligent products. I have worked as a Statistics Data Labeler at MathGPT.ai, Data Analyst, Business Analyst, and AI Research Intern at the Key Laboratory of Artificial Intelligence, OPTICS & Electronics (iOPEN), Xi’an, China. My background combines academic research, software engineering, machine learning, and business-focused problem-solving. Today, I specialize in building complete data ecosystems from research and data acquisition to automated pipelines, cloud infrastructure, databases, web applications, AI agents, and real-time analytics platforms. 🚀 What I Offer 🌐 Data Extraction & Web Scraping Advanced web scraping and data extraction E-commerce scraping (variants, pricing, reviews, shipping, specifications) JavaScript-heavy website scraping API integration and reverse-engineering Large-scale crawling and data collection systems Lead generation and market intelligence Automated data acquisition pipelines ⚙️ Data Engineering & Automation End-to-end ETL/ELT pipeline development Automated data workflows and scheduling PostgreSQL database design and optimization Real-time data processing systems Data warehousing and migration Cloud-based data infrastructure Workflow automation and monitoring 💻 Full-Stack Development & Deployment Data-driven web applications Dashboard and analytics platforms Backend API development Frontend integration with live databases Vercel, Netlify, Cloudflare deployment Azure and Contabo server deployment Production-ready application architecture Scalable cloud infrastructure 🤖 AI Integration & Machine Learning OpenAI GPT integration DeepSeek API integration AI chatbots and AI assistants Custom AI-powered web applications Machine learning model deployment Real-time prediction systems Predictive analytics and forecasting Fine-tuned AI solutions for business workflows 📊 Data Science & Analytics Exploratory Data Analysis (EDA) Statistical analysis and hypothesis testing Time series forecasting Predictive modeling and classification Business intelligence reporting KPI development and performance analysis Outlier detection and anomaly analysis Data visualization and decision-support systems 🛠 Tools & Technologies Python | PostgreSQL | SQL | Pandas | NumPy | Scikit-Learn | TensorFlow | PyTorch | XGBoost | LightGBM | R Programming | MATLAB Selenium | Scrapy | BeautifulSoup | Playwright | Requests | APIs | JSON/XML Parsing | Data Pipelines | ETL/ELT | Automation Systems OpenAI GPT | DeepSeek | AI Agents | Chatbots | LLM Integrations | Machine Learning Deployment PostgreSQL | Supabase | Render | Azure | Vercel | Netlify | Cloudflare | Contabo | Linux Servers Power BI | Tableau | Excel | Google Sheets | Data Visualization | Statistical Analysis | Business Analytics 📚 Portfolio Highlights • End-to-End Data Platforms – Built complete data ecosystems from collection to deployment for multiple businesses • Smart E-Commerce Scrapers – Automated extraction of variants, pricing, shipping, reviews, and product specifications • Real-Time Data Applications – Live systems that continuously collect, process, analyze, and display data • AI-Powered Business Solutions – Integrated GPT and DeepSeek-powered assistants into production websites • PyGWML Package – Open-source Python package for Geographically Weighted Machine Learning • EEG Microstate Classification – Brain state classification research in collaboration with academic institutions • Climatic Trend Forecasting – Advanced time-series forecasting and urban climate analysis 🌟 Why Work With Me? ✅ Full End-to-End Solution Provider – From research and data collection to deployment and AI integration ✅ Strong Background in Data Science, Data Engineering, and Software Development ✅ Experience Building Production-Ready Systems Used by Real Businesses ✅ Expertise in Automation, Cloud Infrastructure, and Real-Time Applications ✅ DataCamp Certified in Data Science & Web Scraping ✅ Excellent Communication and Client Collaboration ✅ Committed to Clean Code, Scalability, and Long-Term Maintainability 💡 Let's Build Something Powerful Whether you need advanced web scraping, automated data pipelines, AI-powered applications, cloud deployment, machine learning solutions, or complete end-to-end data platforms, I can help turn your idea into a reliable, scalable product. 📩 Lets Connect!

As a French Quantitative Algorithmic Trader with dual MSc degrees (Quantitative Finance; Mathematics Applied to ML/DL) and 4+ years of experience, I specialize in building and optimizing end-to-end algorithmic trading systems with a strong focus on backtest quality, strategy design, and deployment readiness. I excel in translating advanced Quantitative Research and Trading Strategies into production-grade Python trading pipelines that deliver consistent, risk-adjusted returns across different asset classes. Core Expertise: Robust Backtesting & Validation - Designed rigorous k-fold walk-forward validation protocols to ensure model generalization and robustness. - Specialized in high-fidelity backtesting frameworks (5+ years of tick/minute data) with transaction costs, slippage, and execution modeling. - Optimised take profits, stop losses and size to improve returns, Sharpe Ratio and Calmar Ratio. Algorithmic Trading Systems in Python : - Proficient in integrating ML/DL models, RL agents, and signal ensembles into live-ready trading codebases. Strategy Design & Innovation - Experienced in alpha factor research, systematic strategy design, and multi-horizon forecasting. - Skilled at combining quantitative finance models (Heston, SABR, volatility surfaces) with modern ML/DL architectures (Transformers, GNNs, RL). Machine Learning & Reinforcement Learning for Trading : -Built RL-based trading agents (PPO, DQ-Net + TFT) achieving Sharpe 1.95 and 20% alpha on BTC spot forecasting. - Developed multi-model ensembles (TFT + Graph Neural Networks) for volatility and alpha prediction. Data Engineering & Feature Integration - Engineered complex feature sets from OHLCV, on-chain metrics, sentiment data (Twitter, Reddit, News), and cross-asset signals. Key Project Highlights: -BTC Perpetual Futures – Live Algo: Designed and deployed a Python strategy achieving Sharpe 1.6 and Calmar 1.6 after costs, with 15% outperformance vs benchmark returns over live trading horizon. - SPY Futures – Multi-TF FVG Strategy: Built a multi-timeframe Fair Value Gap model with positive Sharpe/Calmar, demonstrating robustness and adaptability to equity index futures. -Developed RL agents ( DQ-Net with TFT) with Sharpe 1.95 Calmar 1.6 and 20% alpha in crypto spot forecasting. Technical Toolkit: Languages: Python ML Frameworks: PyTorch, TensorFlow, scikit-learn, Optuna, Vectorbtpro, RLTrading Data Tools: pandas, numpy Domains: Equity index, Crypto/Altcoin Markets, Time-Series Forecasting, RL, Risk Management Education: - MSc Quantitative Finance (Paris Saclay) - MSc Mathematics Applied to Machine Learning & Deep Learning (ENSIIE)