Hello! I'm Subhojit, a seasoned Project Manager, Business Intelligence and AI Architect with 12+ years of experience transforming business challenges into data-powered strategies. From architecting robust BI systems to leading cross-functional teams on cloud-driven data initiatives, I bring deep technical knowledge paired with proven leadership in delivering real business impact. At NeenOpal, a global data consulting firm, I help enterprises modernize, scale, and monetize their data by architecting secure, low‑latency cloud solutions on AWS, Power BI, Tableau, and ML frameworks, etc. From edge‑device telemetry to CEO dashboards, I design end‑to‑end systems that turn streaming data into actionable insight, fast. -----------🔍 𝐖𝐡𝐚𝐭 𝐈 𝐎𝐟𝐟𝐞𝐫 ------------ ✅ End-to-End BI Solutions Designing, architecting & delivering scalable Business Intelligence solutions using tools like Power BI, Tableau, Qlik Sense, and Amazon QuickSight. From data modeling to dashboard deployment – your data journey is covered. ✅ Cloud & ETL Architecture Cloud-native solutions using AWS (EC2, S3, Glue, Lambda) and ETL tools like SSIS for data orchestration, warehousing, and integration. ✅ Data Analytics & Machine Learning Building predictive models and actionable analytics pipelines using Python, SQL, and AWS SageMaker, to uncover insights and drive proactive decision-making. ✅ Project & Delivery Management Hands-on project leadership with Agile & Scrum methodology – managing timelines, stakeholders, and technical teams to deliver outcomes on time and budget. ------------ 💼 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 𝐌𝐞 ------------ ☑️ Results-Oriented Delivery: Spearheaded 50+ successful BI and ML projects across Retail, F&B, Fashion, Advertising, and Home Improvement. ☑️ Full-Stack BI Expertise: From data ingestion to ML models and visualization ☑️ Client-Centric Focus: I take time to understand business pain points and craft bespoke, high-impact solutions that lead to measurable results. ☑️ Certified & Cloud-Ready: Deep expertise across cloud platforms with a strong focus on AWS-native services for modern, scalable data systems. ------------ 🛠 𝐊𝐞𝐲 𝐒𝐤𝐢𝐥𝐥𝐬 ------------ ✔ Generative AI & LLMs: AWS Bedrock, Azure OpenAI, LangChain, RAG, Prompt Engineering ✔ AI & Machine Learning: Python, TensorFlow, PyTorch, SageMaker, Forecasting, Anomaly Detection ✔ SaaS & Full Stack: React, Next.js, Node.js, FastAPI, Multi-Tenant Architecture ✔ Cloud Platforms: AWS (Lambda, Glue, Redshift, IoT, EventBridge), Azure Synapse, Snowflake ✔ BI & Analytics: Power BI, Tableau, QuickSight, Looker, QuickSight ✔ DevOps & MLOps: Docker, Kubernetes, CI/CD, Terraform, Model Monitoring ------------ 🏢 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐞𝐬 𝐒𝐞𝐫𝐯𝐞𝐝 ------------ Retail & E-Commerce | Food & Beverage | Fashion | Digital Ads | Home Improvement | Logistics | Consumer Insights 📞 Let’s Talk! Want a trusted partner to own your data-to-decision journey? Invite me to your job for a complimentary 30-minute consultation. Let’s explore how data can be your competitive edge. 🔑 Keyword Tags AWS Solutions Architect | AWS Architect | Cloud Infrastructure | Digital Transformation | System Design | IoT Analytics | Real‑Time Analytics | Amazon QuickSight | AWS IoT Core | AWS Lambda | AWS Glue | Kinesis | Redshift | Snowflake | Power BI | Tableau | Data Warehouse | Data Engineering | Python | SQL | Machine Learning | Predictive Modeling | Streaming Analytics | DevOps | Terraform

Results-driven Software Engineer currently pursuing a dual State Engineer and Master’s degree in AI & Data Science at ESTIN. With over 10 custom applications developed as a freelance developer, I have increased client operations by up to 30% through tailored solutions for diverse industries, such as clothing stores and barbershops. Proficient in technologies including Flutter, React, and Go, I have built complex full-stack applications like a Zoom clone and cinema system. Fluent in Arabic, English, and French, I bring a multicultural approach to problem-solving. Certified in Google Cloud and Docker, with a commitment to continuous learning and delivering impactful digital solutions.

Most data engineers can write code and connect APIs. But building a data architecture that actually drives business decisions requires understanding the human behavior behind the numbers. With over 14 years of cross-functional experience, I specialize in designing scalable data pipelines and dashboards that turn raw, messy data into clear, actionable business insights. My background is atypical but highly effective: I combine the technical rigor of an Electronic Engineer, the strategic vision of an MBA, and the behavioral insights of a Psychology degree (currently in my final year). This unique mix allows me to go beyond just moving data from point A to point B. I understand the business logic, the financial metrics, and the user behavior you are trying to measure. 🔥 Core Expertise & Tech Stack: Data Engineering & Architecture: Google Cloud Platform (GCP), BigQuery, SQL, Python. ETL/ELT Pipelines: Fivetran, Airbyte, Weld, custom API integrations. Data Transformation: dbt, Dataform. Data Visualization & BI: Looker Studio, Google Sheets, Pandas/Plotly. 📈 Professional Journey Highlights: My experience ranges from acting as a Chief Data Officer (CDO) for software companies to managing complex international operations (including 3 years based in Shanghai, China). I have a proven track record of optimizing architectures, automating workflows, and building data cultures from the ground up. Whether you need to set up a robust data warehouse from scratch, fix broken ETL pipelines, or design dashboards that your stakeholders will actually use, I can help. Let’s connect and discuss how we can build a data architecture that truly serves your business goals.

Hi there! I am an AI ML Lead, Senior Engineer and Developer with over 6 years of experience in designing and implementing cutting-edge AI solutions across various industries and specializing in Natural Language Processing ( NLP ), Large Language Models ( LLM ), Retrieval-Augmented Generation ( RAG ), and Agentic AI. My expertise extends to developing advanced AI-driven medical applications, leveraging state-of-the-art machine learning techniques to drive innovation and efficiency. Passionate about transforming complex challenges into scalable, real-world AI solutions. Brief summary: - have a strong background in mathematics; - implemented ML algorithms for business; - worked on R&D projects; - deployed models to production and monitoring it; - always enhance knowledge in the state-of-the-art AI techniques and read researchings - architecture-oriented, follow best practices to create scalable and mature products - strong organizational, problem-solving and analytical thinking - excellent communication and negotiation skills Domains: - Computer Vision - Natural Language Processing - Data Science - Reinforcement Learning - Generative AI Programming languages and frameworks: Python, Tensorflow, Pytorch, Scikit-learn, Pandas, Numpy, OpenCV, AWS, Flask, Docker. If you are looking for a reliable, creative and experienced AI professional, you have come to the right place - I will eagerly become your longtime partner. Let’s start working together!

I'm a Top Rated quantitative developer on Upwork, currently completing my MS in Data Science at Harvard, with production experience building and shipping algorithmic trading systems across futures, options, and equities. My work spans the full pipeline: from signal research and rigorous backtesting through execution architecture and live broker deployment. Over the years I've collaborated with professional traders, systematic fund managers, and independent CTAs on strategy research, execution system builds, and quantitative infrastructure — working with live accounts and real capital, not toy portfolios. - Research Philosophy Most algorithmic trading research fails before it reaches live markets. The reasons are almost always the same: data snooping bias, fragile parameterization, fill simulation that doesn't reflect actual execution, and strategy logic never stress-tested against regime change. My research process is designed to make it hard to fool yourself. That means strict chronological train/test splits with no parameter bleedthrough, walk-forward optimization over anchored and rolling windows, block bootstrap for inference on autocorrelated returns, and parameter sweep frameworks built to expose fragility rather than maximize backtest metrics. A strategy that only works on one parameterization isn't a strategy, it's a coincidence. I care about robustness across parameter space, regime stability, and understanding exactly why a signal works before scaling it. I work extensively in QuantConnect's LEAN engine for research-grade backtesting and live account deployment, though deployment targets vary by strategy and client stack. IB TWS via ibapi, Tradovate, and NinjaTrader are all in regular rotation depending on execution requirements. I build custom analytics layers on top of backtest output: Sharpe decomposition, drawdown attribution, execution cost modeling, and signal decay analysis, because standard tearsheet metrics rarely tell the full story. - Strategy Coverage My research spans futures (NQ, ES), SPX and index options, ETFs, and crypto. Strategy types I've built and validated in production include intraday momentum and trend-following systems, mean reversion and stat-arb frameworks, breakout and scalp architectures with dynamic sizing tiers, options strategies including iron condors, defined-risk vertical spreads, 45-DTE and 0DTE SPX structures with delta-based hedge logic, and GEX (gamma exposure) driven directional frameworks using open-interest-weighted dealer positioning data. It's an area where the signal literature is still thin and where getting the methodology right matters more than most people acknowledge. - Execution Engineering The research-to-live gap is where most systems break. I build execution infrastructure that closes that gap: Interactive Brokers TWS via ibapi with state machine architectures, order ladder geometry, true breakeven calculations with commission and slippage factored in, and hedge math for multi-leg positions. On the NQ/ES side I've built and audited scalp bot execution logic on Tradovate, integrated Databento for professional tick data pipelines with proper validation against reference data, and developed Pine Script strategies and indicators on TradingView for signal prototyping before committing to full implementation. I'm also familiar with NinjaTrader's execution environment and ATM framework. Code I deliver is production-standard: structured logging, explicit edge-case handling, clean separation of signal and execution layers, and documented at a level where the system is maintainable after handoff. - What I Work On: - Strategy Research & Backtesting: QuantConnect/LEAN, Backtrader, Zipline, VectorBT, QuantLib, Python - Execution Systems: IB TWS/ibapi, Tradovate API, NinjaTrader, REST/WebSocket broker integrations, FIX Protocol - Retail Platform Development: MQL4/MQL5 (MetaTrader 4/5), Pine Script (TradingView), NinjaScript (NinjaTrader 8), EasyLanguage (TradeStation), ThinkScript (Thinkorswim), cAlgo/C# (cTrader), AFL (AmiBroker) - Broker APIs: Interactive Brokers, Alpaca, TD Ameritrade, Tradovate, Oanda, Databento - Crypto Platforms & APIs: Binance, Bybit, OKX, Kraken, Coinbase Advanced Trade, Bitfinex, Deribit (options/derivatives), KuCoin, Gate io, Freqtrade, Hummingbot, 3Commas, Pionex, Gunbot, ccxt (unified exchange library) - Statistical Testing: Walk-forward testing, parameter sweep analysis, Monte Carlo simulation, bootstrap inference - Full-Stack Delivery: Data ingestion → signal research → backtesting → live deployment

I am a 🔹Top-Rated Freelancer🔹 offering services in statistical learning, predictive modelling, Dashboard design, MASTERS/PHD survey design and data analysis, ⭐𝗧𝗼𝗼𝗹𝘀: 𝗥𝗦𝘁𝘂𝗱𝗶𝗼❟ 𝗣𝘆𝘁𝗵𝗼𝗻❟ 𝗝𝗮𝗺𝗼𝘃𝗶❟ 𝗝𝗔𝗦𝗣❟ 𝗘𝘃𝗶𝗲𝘄𝘀❟ 𝗜𝗕𝗠 𝗦𝗣𝗦𝗦❟ 𝗣𝗢𝗪𝗘𝗥𝗕𝗜❟ 𝗘𝗫𝗖𝗘𝗟 ⭐Services I Provide: 🔷 Statistical Modeling & Data Analysis From hypothesis testing to regression analysis, I provide clean, accurate, and interpretable results using R, Python, SPSS, and Excel. 🔷 Machine Learning & Predictive Analytics I build, test, and fine-tune models such as Random Forest, KNN, Decision Trees, and Neural Networks to uncover trends and support intelligent decision-making. 🔷 Time Series Forecasting Need to predict what comes next? I offer forecasting models for stock prices, sales trends, healthcare data, and more. 🔷 Data Visualization & Insights I design clean and compelling data visualizations using ggplot2, seaborn, and Power BI—turning complex results into clear, engaging visuals. 🔷 Graduate Thesis & Dissertation Support With years of experience mentoring students, I help Master's and PhD candidates navigate data analysis, research design, and writing with clarity and confidence. 🔷 Quantitative Research Consulting Whether you're analyzing survey results, building a classification model, or identifying trends in time series data, I help structure your analysis and interpret results with precision. 📊 Data Types I Work With 🔷 National and regional survey data (health, labor, finance, education) 🔷 Time series datasets for forecasting and anomaly detection 🔷 Panel data across longitudinal studies 🔷 Business intelligence data 💡 Why Choose Me? 🔷 Graduate-level statistician 🔷 Fast, clear communication and expert-level documentation 🔷 Committed to accuracy, transparency, and client satisfaction Your consideration is highly appreciated.

Expert-Vetted Gen AI Engineer | Harvard and Columbia Alumni (Top 1% of Freelancers on Upwork) I am a highly experienced Generative AI Engineer who has worked with clients across multiple industries including finance, academia, e-commerce, construction, medicine, and web design. I provided high-quality solutions for all of my clients, earning me outstanding reviews and a 100% Job Success Rating. My areas of expertise include Large Language Models (LLMs), Generative AI, Chatbots, Data Science, AI Dashboard Development, Natural Language Processing, Data Visualization, and Statistics. In addition to my experience as an AI Engineer, I also have deep knowledge in grant writing, academic publishing, and clinical data analysis, having both written successful NIH and biotech grants and published 10+ manuscripts in high-impact academic journals such as Nature and Gastroenterology. SKILLS: * Extensive Experience with Prompt Engineering with many different LLMs such as OpneAI, Claude, Mistral, Gemini, Llama, Gemma, CodeLama, and Vicuna. * Built 20+ AI dashboards with Streamlit, Gradio, and HuggigngFace for clients to easily access solutions * Created Vector Databases and Retrieval-Augmented Generation Software to train LLMs on personal data such as PDFs, Word Documents, YouTube Videos, Images, and Excel Spreadsheets. * Proficient in leading AI solutions to production using AWS, GitHub, Langchain, LlamaIndex, LangSmith, LangFuse, and other AI tools. * Strong background in programming languages (Python, R, Javascript, SQL) and Data Science/Machine Learning frameworks (TensorFlow, Keras, PyTorch, scikit-learn, numpy, pandas) * Expertise in EHR, ICD-10 codes, clinical database management, clinical data analysis, and HIPAA compliance * Experience with Business Intelligence platforms such as Tableau, PowerBI, and Excel PROJECTS/ACCOMPLISHMENTS: * Co-Founder and CTO of a biotech company, Daldot which was acquired by Nutromics, an Australian MedTech company in 2021 * Developed the AI Algorithm for Shopify App that gained 10K+ users within a month * AI TikTok Influencer with 10K+ followers and 1M+ likes * Columbia University SEAS GSA Black History Month Alumni Spotlight 2023 * 2nd Place in the Columbia University Data Science Institute COVID-19 Data Challenge * Published 10+ manuscripts in high-impact journals such as Nature and Gastroenterology SPEAKING ENGAGEMENTS: * Guest Lecturer at Columbia University, Cornell Tech, Roux Institute, and Founder Institute for entrepreneurship, AI, and freelancing. * Developed a course on emotional intelligence for startup founders at Harvard University with 1,000+ students enrolled. * Presented research at the American Society of Clinical Oncology (ASCO) and Columbia University Data Science Institute Machine Learning in Science & Engineering Conference. EDUCATION: * Master's in Data Science from Columbia University * Bachelor's in Biophysics from Harvard University I have a 100% success rate in provided top-tier solutions across diverse sectors. Whether you need a custom solution or expert guidance, I am committed to leveraging the power of AI to elevate your business to the next level. Let's innovate together!

I'm a Data Professional, Data Scientist, Machine Learning and AI engineer, and Software Engineer with 10+ Years of Experience in Tech. I leverage tech and data to drive insights and build intelligent systems using Data, ML and AI using Python, R, Tableau, PowerBI, Data Studio, as well as scalable software systems in Django, PostgreSQL, MySQL and APIs. In my experience, I have been helping businesses and individuals build data and software systems such as CRMs, Enterprise Software, Web Apps, automation for marketing and sales processes, digital marketing and use of AI in driving Business Productivity. Whether you need data analysis, data extraction, data mining, exploratory analysis, machine learning, or AI model and software app development or CRM design and implement, I can help. 1. Proficient in Python, R, SQL, TensorFlow, PyTorch, Airflow, PowerBI, Tableau, and Scikit-learn 2. Experienced in data management, data analysis, data mining, data visualization, and building end-to-end machine learning pipelines; conversant with design and management of CRMs (Zoho, PipeDrive, Hubspot, Salesforce, Freshsales) and automation. 3. Strong background in statistical modeling, deep learning, and natural language processing 4. I am a Full stack software engineer with experience in Django, SQL and APIs. Let's connect and grow together😊

I am pursuing my Master's in Applied Mathematics and since the beginning of my undergrad I've been trying to develop a very horizontal, interdisciplinary formation, which is most organic to me since my interests span a wide range of -- often intertwined -- topics. My core technical interests are within the grand areas: Artificial Intelligence, Pure & Applied Mathematics, Theoretical Computer Science, Complex Systems & Complexity Theory, and Network Science. I have an extensive mathematical background and solid programming experience. A driving problem that could be said to be the connecting thread between all of the aforementioned interests is that of further understanding "intelligence" as an emergent phenomenon that arises from the dynamics found within and between complex adaptive systems.

🚨 Struggling with manual reports, messy data, or slow decision-making? I help businesses automate their data workflows, dashboards, and reporting systems — saving hours every week and reducing errors significantly. With 40+ projects delivered and Top Rated Plus status on Upwork, I specialize in turning complex data processes into clean, automated systems using **Alteryx, Python, and modern BI tools**. 🚀 What I can help you with: * Automating repetitive data workflows (Alteryx / Python) * Building dashboards (Tableau, Power BI) for faster decision-making * Cleaning, transforming, and structuring messy data * Migrating legacy reports (Excel → BI tools) * Designing scalable data pipelines 🤖 Moving Beyond Traditional BI: I’m actively building AI-powered data systems, including: * AI-driven insights & reporting * Workflow automation using AI * Exploring AI Agents & Agentic workflows for business processes 💡 What you get: * Faster reporting (hours → minutes) * Reduced manual effort * Reliable, structured data systems * Clear insights for better decisions