Hire the Best Decision Tree Specialists

DATA SCIENTIST — everything I build, you can verify the math. I deliver transparent, auditable data models where every number can be checked. Specializing in quantitative research, statistical modeling, Data insights and automation. QUANTITATIVE RESEARCH & PORTFOLIO CONSTRUCTION : I build and backtest equities, with live execution and kill switches on Alpaca where needed. Position sizing, risk allocation, rebalancing logic, all of it grounded in the math, not gut feel. Quick example of how I think: a momentum strategy covering 145 stocks was delivering 41% CAGR. Expanding to 245 stocks dropped it to 36%. Counterintuitive. The root cause: New stocks were selected on hot recent momentum, so by entry their cycle was already done. Built a 5-filter Monte Carlo system, tested 700+ parameter combinations, to identify which satellites are early-cycle vs peaked. Result: 43%+ CAGR with lower drawdown than the 145-only baseline. The problem wasn't the strategy. It was the timing of entry. Another example: I built a live MBS (Mortgage-Backed Securities) forecasting and trading system for a fund client, covering 265+ cohort securities across weekly, monthly, and quarterly return horizons. The interesting part wasn't the ML, it was the feature design. Standard technical indicators on bond prices are noise. What actually drives MBS price movements is duration, convexity, prepayment rates, regime variables like curve steepness, VIX, and Fed MBS holdings. Every feature built from first principles, nothing borrowed from a vendor that can't be verified. This is where I spend most of my time. Systematic backtests, portfolio construction, Monte Carlo optimization. No black boxes, no ML hype every output can be checked in a spreadsheet. Not "add more data." Find the actual structure driving returns, and build features that reflect it. DATA SCIENCE & ANALYTICS I've worked across real estate, e-commerce, and financial analytics, usually called in when a team has data but no clear answer yet. I focus on getting to a decision you can act on, not a 40-slide deck. Results worth mentioning: ML automation cut a client's data processing from 286 days to 1 day, after they'd run the same manual process for two years without realizing it was automatable Ad spend attribution model that improved campaign ROI by 25% WHAT MAKES ME DIFFERENT ▸ I show my work. Every model, every analysis, every number comes with the method behind it, so you're never trusting a black box ▸ I'd rather tell you a strategy doesn't hold up than build you something that looks good and fails in real world. ▸ I scope real problems fast: send me what you're working with and I'll tell you within 24 hours if and how I can help

🏅 Top Rated AI/ML Expert on Upwork (Top 1%) 🏅 AI Product Engineer | LLM Applications | Generative AI | Agentic Workflows 🏅 10+ Years of Experience | Built Solutions for Startups, Enterprises & Global Clients 🏅 Experience Across Microsoft, Google, American Express & High-Growth Startups 🏅 Expert in Python, OpenAI, Claude, LangChain, LangGraph, AWS, SQL 🔹 LLM Applications & Generative AI Products I build end-to-end LLM-powered applications that solve real business problems—from idea to deployment. My work includes document intelligence systems, AI copilots, enterprise search, summarization engines, Q&A systems, and workflow automation platforms. Built solutions for: ✔ Due diligence copilot for investment workflows ✔ Legal AI research platforms ✔ Resume/CV parsing applications ✔ AI-powered document summarization systems ✔ Knowledge retrieval platforms using RAG 🔹 AI Agents & Workflow Automation I design intelligent AI agents that automate repetitive workflows and improve operational efficiency. Examples include: ✔ Multi-agent workflows ✔ AI automation using OpenAI, Claude, LangChain & LangFlow ✔ Process automation using n8n ✔ Document processing pipelines ✔ Internal business workflow automation 🔹 NLP & Custom Machine Learning Solutions Strong background in NLP and machine learning beyond LLMs, including: ✔ Named Entity Recognition ✔ Classification Models ✔ Clustering Models ✔ Recommendation Systems ✔ Text Processing Pipelines ✔ Custom ML model development 🔹 Predictive Analytics & Risk Modeling My foundation comes from years of building machine learning models for large enterprises including Google and American Express. Experience includes: ✔ Credit risk modeling ✔ Fraud analytics ✔ Customer segmentation ✔ Forecasting ✔ Marketing analytics ✔ Behavioral modeling 💼 Whether you're a startup building your first AI product or an enterprise looking to integrate Generative AI into existing workflows, I can help with: AI Strategy → Architecture → MVP Development → Deployment I combine deep analytical expertise with hands-on experience building real-world AI products that businesses actually use.

Stop Wasting Millions on AI Models Crippled by Bad Data. Your AI model is only as powerful as its training data. Inconsistent data annotations sabotage performance, costing you weeks and millions in lost ROI. If your team is cleaning Machine Learning datasets instead of building, you need a better solution. As a Top Rated Plus expert, I deliver Training Ready Intelligence. My mission: transform your raw training data into high fidelity, structured assets for peak AI model performance in Computer Vision, NLP, and Machine Learning. I specialize in clean, reliable data annotation for images, video, and text. I ensure data quality directly impacts your model accuracy and bottom line. I've managed massive data labeling projects, consistently exceeding expectations. Why elite AI teams choose me: Guaranteed Accuracy: 100% pipeline ready data annotation, every time. No re work, no debugging. Zero Management Overhead: You define; I execute with precision and autonomy. Focus on AI development, not data prep. Accelerated ROI: Cut training cycles, deploy faster. Transform raw data into a competitive advantage. My Core Expertise: Image Annotation: Bounding Box, Polygon, Semantic Segmentation, Keypoint (Computer Vision) Video Annotation: Object Tracking, Event Detection (Computer Vision) Text Annotation: NER, Sentiment Analysis, Classification (NLP) Data Labeling & Dataset Preparation Ready to elevate your AI project? Click Message. Let's build the robust training data foundation your AI models deserve. Stop settling for "good enough" data annotation; get it right the first time. Best Regards, Parwiz

MOST AI AND BI INITIATIVES FAIL because the underlying data foundation is broken. I am an Expert-Vetted Principal Architect (Top 1%) and 15x US Patent Holder who builds "Agentic" data foundations. I specialize in turning multi-source chaos into a Single Source of Truth that doesn't just report data, it reasons over it. My latest build, AgentMaestro, achieved 97% accuracy in the volatile Miami Real Estate market by replacing legacy "Black Box" ML with a "Two-Brain" Reasoning Architecture. I HELP AMBITIOUS ORGANIZATIONS SOLVE THREE CRITICAL PROBLEMS: 1. COST & LATENCY: I re-engineer legacy warehouses using Dataform and modern ELT logic to reduce cloud bills by 30%+ while achieving sub-2-second dashboard latency. 2. DATA INTEGRITY & ATTRIBUTION: I unify fragmented silos (Shopify, Meta, CRM, GTM/CAPI) into high-integrity Customer Data Platforms (CDP) to provide 100% visibility into ROI and Attribution. 3. REASONING-AS-A-SERVICE (RaaS): I move beyond simple "predictive modeling" into Agentic AI. I deploy LLM-driven reasoning engines (Vertex AI) that provide "Glass Box" audit trails for high-stakes decision-making. THE "MAESTRO" DIFFERENCE: I am not a "task-taker." I am a strategic partner who owns the entire data lifecycle. I design the proprietary logic that ensures your data is an asset, not a liability. Let's connect to architect your Single Source of Truth. CERTIFICATIONS - Google Cloud Professional Data Engineer - Google Cloud Professional Machine Learning Engineer - Google Data Analytics Professional - Google Business Intelligence Professional SKILLS Cloud Platforms: - Google Cloud Platform (GCP) Data Warehousing & Big Data: - BigQuery - BigLake - PostgreSQL - MySQL - SqlServer Data Modeling: - Dataform - dbt Machine Learning & AI: - BigQueryML - Vertex AI - TensorFlow - H2O - Caret - Scikit-learn - ML Model Development & Deployment Business Intelligence & Visualization: - Looker - Looker Studio - Google Sheets - Apache Superset - Airtable Programming Languages: - SQL - R - Python Data Engineering ELT & ETL: - Dataflow - Cloud Pub/Sub - Data Pipelines - Dataform - Cloud Functions. Ecommerce Platforms: - Shopify Data Science: - Predictive Analytics - Customer Segmentation - Data Mining - Statistical Analysis - RFM Analysis - Contribution Analysis - LTV - Time series forecasting - Recommender Systems

Hi, I'm Umar — a business-driven Data Scientist, Machine Learning Engineer, Data Analyst, and Business Analyst helping organizations transform data into actionable insights, intelligent solutions, and better business decisions. I specialize in: Predictive Modeling & Machine Learning with Python (Scikit-learn, TensorFlow, Pandas) Data Analysis & Business Intelligence using SQL, Excel, Power BI, and Tableau Interactive Dashboards & KPI Reporting for executive decision-making Data Cleaning, Exploration, Feature Engineering, and Statistical Analysis Business Analysis, Requirements Gathering, Process Improvement, and Data-Driven Decision Support With over 3 years of experience, I've helped organizations: * Build predictive models for customer churn, demand forecasting, fraud detection, and risk analysis * Design interactive dashboards that track KPIs and business performance * Analyze large datasets to uncover trends, patterns, and opportunities for growth * Automate reporting processes to improve efficiency and reduce manual work * Translate complex business requirements into data-driven solutions that deliver measurable results **What makes me different?** I bridge the gap between business objectives and technical solutions, ensuring every project delivers real business value. I combine expertise in analytics, machine learning, and business analysis to solve complex business problems. I communicate technical findings in a clear, actionable way so stakeholders can make confident, data-driven decisions. Whether you need advanced analytics, machine learning models, business intelligence dashboards, or business analysis support, I'm here to help turn your data into smarter decisions and measurable business outcomes. Let's connect and discuss how I can help your business succeed.

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.