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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

I'm Vishwajeet Panda, a highly motivated and results-oriented tech professional with a passion for innovation and a proven track record of success. As a winner of the Smart India Hackathon in both 2022 and 2023, I possess strong technical expertise in Machine Learning (ML), Deep Learning (DL), and web development. My diverse skillset encompasses Python, TensorFlow, Keras, Scikit-learn, and more. I also have experience with MLOps, Flask, OpenCV,and web development frameworks. Here's what sets me apart: * My victories in Hackathons showcase my ability to tackle complex challenges and deliver innovative solutions, in tight deadlines. * My top priority is high quality work and I thrive on building successful partnerships and exceeding expectations. Ready to discuss your project? Leveraging my skills and experience to bring your vision to life. Contact me today to discuss how I can contribute to your success. Email: panda18vishu@gmail.com

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, AWS Step Functions, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!

I help startups and enterprises build production-ready AI products, intelligent automation systems, LLM applications, and data-driven SaaS platforms. Strong expertise in Artificial Intelligence, Machine Learning, Data Science, Generative AI, Computer Vision, NLP, and Full Stack Development. I build complete AI solutions—from data engineering and model training to scalable APIs, modern web applications, and cloud deployment. 🚀 Core Expertise AI, Machine Learning & Data Science -------------------------------------------- Machine Learning, Deep Learning, Generative AI PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM NLP, Computer Vision, OCR YOLO, OpenCV Time Series Forecasting Predictive Analytics Recommendation Systems Classification, Regression, Clustering Feature Engineering Model Optimization & Fine-tuning Statistical Analysis A/B Testing Data Mining Explainable AI (XAI) LLMs & Agentic AI ---------------------- OpenAI (GPT-4o/o3/o4) Claude Gemini Llama Mistral DeepSeek Grok LangChain LangGraph LlamaIndex CrewAI AutoGen AI Agents Multi-Agent Systems Agentic Workflows MCP (Model Context Protocol) RAG Pipelines Prompt Engineering Function Calling Structured Outputs Semantic Search Embeddings Fine-tuning Data Engineering --------------------- ETL / ELT Pipelines Apache Airflow Apache Kafka Data Warehousing Data Lakes Batch & Real-time Processing Data Cleaning Feature Stores Web Scraping Selenium Scrapy Pandas NumPy PySpark Vector Databases ---------------------- Pinecone Weaviate Milvus ChromaDB FAISS Qdrant Full Stack Development ---------------------------- Python FastAPI Django Flask Node.js Express.js NestJS React Next.js TypeScript JavaScript Tailwind CSS REST APIs GraphQL Microservices WebSockets Databases ------------- PostgreSQL MySQL MongoDB Redis Elasticsearch DynamoDB Firebase Cloud & DevOps ------------------- AWS Azure Google Cloud Platform (GCP) Docker Kubernetes Terraform GitHub Actions CI/CD Linux Nginx I Build ✔ AI SaaS Platforms ✔ AI Agents & Multi-Agent Systems ✔ LLM Applications ✔ RAG Knowledge Assistants ✔ AI Chatbots & Copilots ✔ Machine Learning Models ✔ Computer Vision Solutions ✔ Predictive Analytics Platforms ✔ Recommendation Engines ✔ Fraud Detection Systems ✔ Forecasting Models ✔ Document Intelligence & OCR ✔ Data Pipelines & ETL Systems ✔ Enterprise Dashboards ✔ Cloud-native Applications Why Hire Me End-to-end ownership from idea to production Strong AI, ML, Data Science, and Software Engineering expertise Scalable architecture designed for real-world production Clean, maintainable, and high-performance code Fast communication and long-term technical partnership Keywords AI Engineer • Machine Learning Engineer • Data Scientist • Generative AI • Full Stack AI Developer • LLM Engineer • Python Developer • FastAPI • Django • React • Next.js • OpenAI • Claude • Gemini • LangChain • LangGraph • AI Agents • RAG • NLP • Computer Vision • YOLO • PyTorch • TensorFlow • Scikit-learn • XGBoost • Data Engineering • ETL • Airflow • Kafka • Vector Database • Pinecone • PostgreSQL • Docker • Kubernetes • AWS • Azure • GCP • SaaS Development If you're looking for an engineer who can design, build, deploy, and scale AI-powered products that solve real business problems, I'd be happy to discuss your project.

🏆 𝐄𝐱𝐩𝐞𝐫𝐭-𝐕𝐞𝐭𝐭𝐞𝐝 — 𝐓𝐨𝐩 𝟏% 𝐨𝐟 𝐔𝐩𝐰𝐨𝐫𝐤 𝐓𝐚𝐥𝐞𝐧𝐭 💰 $𝟓𝟎𝟎𝐊+ 𝐄𝐚𝐫𝐧𝐢𝐧𝐠𝐬 | 𝟖𝟎+ 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 | 𝟖,𝟎𝟎𝟎+ 𝐇𝐨𝐮𝐫𝐬 ⭐ 𝟏𝟎𝟎% 𝟓-𝐒𝐭𝐚𝐫 𝐑𝐞𝐯𝐢𝐞𝐰𝐬 | 𝐙𝐞𝐫𝐨 𝐍𝐞𝐠𝐚𝐭𝐢𝐯𝐞 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 ☁️ 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐞𝐝 𝐀𝐖𝐒 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 I am a 𝐋𝐞𝐚𝐝 𝐀𝐈/𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 with 10+ 𝐲𝐞𝐚𝐫𝐬 of experience across 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐍𝐋𝐏, 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐋𝐋𝐌𝐬, 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬, 𝐕𝐨𝐢𝐜𝐞 𝐀𝐠𝐞𝐧𝐭𝐬, and production AI engineering. Clients rely on me to build 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐀𝐈 𝐬𝐲𝐬𝐭𝐞𝐦𝐬- not just demos or API wrappers. My focus on reliability, scalability, security, and measurable business outcomes has helped me maintain 𝟏𝟎𝟎% 𝟓-𝐬𝐭𝐚𝐫 𝐫𝐞𝐯𝐢𝐞𝐰𝐬 with no negative feedback on Upwork, a track record rarely seen among freelancers with a comparable volume of completed work. I can develop a complete 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐀𝐈 𝐩𝐫𝐨𝐝𝐮𝐜𝐭- from solution architecture and model development to backend, frontend, cloud deployment, monitoring, and scaling- or integrate an AI solution directly into your existing applications and business workflows. 🎙️ 𝐀𝐈 𝐕𝐨𝐢𝐜𝐞 𝐀𝐠𝐞𝐧𝐭𝐬 ➜ Built and productionized multiple real-time AI voice agents using 𝐋𝐢𝐯𝐞𝐊𝐢𝐭 ➜ AI voice receptionists, customer support agents, sales agents, appointment-booking agents, and voice assistants ➜ Low-latency speech-to-speech conversations, natural turn-taking, interruption handling, and voice activity detection ➜ Function calling, call routing, telephony integration, human handoff, and workflow automation ➜ Integration with STT, TTS, LLMs, APIs, CRMs, databases, and enterprise knowledge bases ➜ LiveKit Agents, Deepgram, OpenAI Realtime, ElevenLabs, Amazon Polly, Claude, and AWS Bedrock 🤖 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 ➜ Agentic AI systems using LangGraph, AutoGen, CrewAI, and custom orchestration frameworks ➜ Multi-agent workflows, tool calling, memory, planning, human-in-the-loop, and autonomous task execution ➜ Custom AI chatbots and copilots using OpenAI, Claude, AWS Bedrock, Llama, Mistral, and Qwen ➜ RAG pipelines, semantic search, hybrid retrieval, reranking, vector databases, and knowledge assistants ➜ Document intelligence, natural-language-to-SQL, structured data extraction, and workflow automation ➜ LLM evaluation, guardrails, prompt engineering, structured outputs, and hallucination reduction 📊 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 & 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 ➜ Predictive modelling, classification, regression, clustering, and anomaly detection ➜ Time-series forecasting, demand forecasting, customer segmentation, and churn prediction ➜ Recommendation engines, ranking systems, personalization, and similarity matching ➜ Sentiment analysis, text classification, topic modelling, summarization, and information extraction ➜ Computer vision, object detection, image classification, motion tracking, and scene recognition ➜ Feature engineering, model evaluation, explainable AI, experimentation, and MLOps 🧠 𝐋𝐋𝐌 𝐅𝐢𝐧𝐞-𝐓𝐮𝐧𝐢𝐧𝐠 & 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 ➜ Fine-tuning LLMs for domain adaptation, Q&A, classification, extraction, legal, medical, and enterprise use cases ➜ Synthetic dataset generation, training-data preparation, and evaluation frameworks ➜ LoRA, QLoRA, supervised fine-tuning, and instruction tuning ➜ Production deployment using vLLM, Hugging Face, AWS, GCP, RunPod, Docker, and serverless infrastructure ☁️ 𝐀𝐖𝐒 & 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐀𝐈 ➜ AWS Bedrock, SageMaker, Lambda, API Gateway, ECS, ECR, S3, RDS, DynamoDB, and OpenSearch ➜ Secure, scalable, multi-tenant AI applications and data pipelines ➜ Python, FastAPI, PostgreSQL, Redis, MongoDB, and vector databases ➜ Monitoring, model evaluation, latency optimization, cost control, and production support Whether you need a complete 𝐀𝐈 𝐒𝐚𝐚𝐒 𝐩𝐫𝐨𝐝𝐮𝐜𝐭, an 𝐀𝐈 𝐜𝐨𝐩𝐢𝐥𝐨𝐭, a 𝐯𝐨𝐢𝐜𝐞 𝐚𝐠𝐞𝐧𝐭, a predictive ML system, or an AI capability integrated into your existing workflow, I can take it from idea to a secure, scalable, and production-ready solution.

Data Engineer & AI Developer | 3+ Years Financial Industry Experience I build data pipelines, AI-powered applications, and automation systems that run reliably at scale. My background spans web scraping, LLM integration, computer vision, betting automation, and full-stack data dashboards — delivered to clients across the US, UK, Europe, and Japan. 💼 Background — 3+ years at a leading Indian bank building risk models, credit scorecards, and AutoML pipelines — PG Diploma in Big Data Analysis ⚡ What I Deliver — Web scrapers handling 1.2M+ URLs and 120K daily pipelines — LLM/AI apps using GPT-4, Gemini, LangChain, RAG, Text-to-SQL — Full Betting automation for horse racing, golf, and football signals — Computer vision pipelines with YOLOv8 and PaddleOCR — Streamlit dashboards, risk scorecards, and AutoML tools 🏆 Notable Work — PitchBook scraper — 1.2M URLs — Njuskalo — 120K daily real estate listings — Text-to-SQL architecture — BetFare — full Betfair automation — LLM Notebook — $1,420 solo delivery — Anti-bot bypass systems 🛠️ Stack Python · Playwright · Selenium · GPT-4 · Gemini · LangChain · Streamlit · PySpark · SQL · YOLOv8 · PaddleOCR · FastAPI · Betfair API · n8n Clean code. Clear communication. Delivered on time.