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Need an AI system that actually makes it to production — not another demo that breaks under real users? That's exactly what I build. I'm an AI Engineer with a track record of shipping end-to-end LLM, RAG, and autonomous agent systems for enterprise clients in finance and insurance — the kind of environments where security, compliance, and hallucination control are non-negotiable. Most AI projects stall at the proof-of-concept stage. My focus is the opposite: taking ideas from prototype to scalable, reliable production on AWS and GCP. ━━━━━━━━━━━━━━━━━━━━━━ WHAT I CAN DO FOR YOU: 🤖 AI Agents & Agentic Workflows Design and orchestration of autonomous agents (LangChain, LangGraph, Google ADK) that automate complex, multi-step business processes. 📚 RAG & LLM Applications Retrieval-Augmented Generation systems, chatbots, and LLM integrations built with hallucination mitigation and enterprise-grade reliability. GPT, Llama, HuggingFace, fine-tuning & prompt engineering. 📊 Machine Learning in Production Predictive, scoring, churn, and fraud-detection models (XGBoost, CatBoost, LightGBM, Deep Learning) — deployed, monitored, and built to hold up under scrutiny. ⚙️ MLOps & Data Pipelines Scalable pipelines with Kedro, Apache Airflow & Cloud Composer. Full deployment on AWS (SageMaker, Bedrock) and GCP (Vertex AI). ━━━━━━━━━━━━━━━━━━━━━━ WHY CLIENTS TRUST ME: ✓ Real production experience at major financial institutions (Scotiabank, BCP, Banco Falabella) ✓ Built a fraud-detection scoring system with 5.6x lift over random selection for a national-scale energy project (Inter-American Development Bank) ✓ AWS Certified Machine Learning Engineer + MIT MicroMasters in Statistics & Data Science ✓ Generative AI instructor — I translate complex technical work into language business stakeholders actually understand I work well with founders, product teams, and enterprises who need someone who can own a problem end-to-end: architecture, build, deployment, and the hard conversations about what's actually feasible. If you're looking for an AI engineer who ships reliable systems — not just impressive demos — let's talk. Send me a message with what you're working on and I'll tell you honestly how I can help.

I am a rising junior at New York University pursuing a double major in Data and Computer Science. I am experienced in data collection, cleaning, and analysis. Proficient in python, java, as well as SQL.

🏆 Microsoft Certified Data Engineer and Analyst 🏆 Senior Data Engineer and Analyst with over 10 years of experience I am a Senior Data Engineer and Analyst specializing in building scalable data pipelines, designing data architectures, and delivering impactful dashboards. My expertise spans data integration, transformation, and analytics, ensuring optimized and actionable solutions tailored to business needs. Expertise includes: 🔶 Data Engineering & Architecture: ● ETL Mastery: Expert in cloud-based ETL tools such as AWS Glue, Azure Data Factory, GCP Data Fusion, and Snowflake ELT workflows for seamless data ingestion, transformation, and loading. ● SQL Proficiency: Mastery of SQL query optimization, advanced joins, window functions, and stored procedures across T-SQL, MySQL, PostgreSQL and Snowflake SQL (micro-partition pruning, clustering, semi-structured data queries). ● Data Pipeline Orchestration: Experienced in using workflow management tools like Apache Airflow and Snowflake Tasks to automate and monitor data pipelines efficiently. ● Data Warehousing: In-depth experience with Snowflake, Redshift, and BigQuery, including dimensional modeling and normalization best practices. 🔶 Data Analysis & Dashboard Development: ● Power BI: Skilled in creating dynamic, interactive reports using centralized datasets, PowerQuery, DAX measures, and Python scripting for complex data transformations. ● Tableau: Advanced expertise in integrating diverse data sources, creating calculated fields, and developing visually compelling dashboards. ● Looker: Proficient in LookML for data modeling, custom visualization, and embedding analytics for seamless integration with business workflows. ● Real-Time Insights: Delivered actionable dashboards connected directly to cloud-based sources for up-to-date analytics. 🔶 Cloud Platform Expertise: ● AWS: Advanced knowledge of Lambda, Glue, S3, and Redshift for scalable and secure data processing. ● Azure: Extensive experience with Function Apps, Synapse, Data Factory, and Data Lake Gen 2 for robust data solutions. ● GCP: Expertise in BigQuery, Cloud Functions, Data Fusion, and Looker for analytics and data management. ● Snowflake: End-to-end warehouse development including schema design, performance tuning, ELT, RBAC security, semi-structured data (VARIANT), Streams & Tasks, external tables, and cost optimization 🔶 Data Governance & Transformation: ● Strong Python scripting skills for automation, API integration, and advanced data cleansing. ● Hands-on experience with tools like Pandas Profiling, OpenRefine, and Trifacta Wrangler for data profiling, quality assurance, and anomaly detection. ● Proficient in implementing secure access controls using IAM roles, Lake Formation, and APIs, as well as Snowflake RBAC, masking policies, and secure data sharing for governance and compliance. 🔶 API Integration & Automation: ● Built and managed data pipelines for platforms such as Stripe, AWS, and Google Analytics. ● Integrated APIs to extract, transform, and load data seamlessly into analytics platforms. ● Automated complex workflows using Python and cloud-native tools, ensuring efficiency and scalability. I am passionate about delivering data solutions that not only meet but exceed client expectations. Let’s collaborate to turn your data into a powerful asset for strategic decision-making! Thank you for your time!

I am a multilingual Data Scientist with Bachelor of Engineering in Mechatronics. I have experience with data science using Python, ML, and am continuing to improve my knowledge. I am able to write clear and concise code, looking for scalability. I work and perform well in a team setting as well as under pressure. I am looking for more experience working as a machine learning engineering, I did many projects about machine learning and I have a specialization in Data Science and Machine Learning.

I'm a product-minded data scientist who works across product, data, and design. I don't just analyze data, I use it to make products better, from content strategy to UI to AI-powered workflows. My background is in data science and machine learning (Kaggle Notebook Legacy Grandmaster, former #29 worldwide), but over the past few years, my work has expanded well beyond modeling. I now operate at the intersection of product, content, design, and AI — owning problems end-to-end rather than one narrow slice. What I actually do day to day: I build and improve digital products, designing interfaces, prototyping with AI tools, preparing and formatting content for CMS import at scale, creating AI-powered workflows, and using data to guide every decision. Most of my recent work has been in edtech, but the approach applies to any product team that needs someone who can think across layers and ship. Where I'm strongest: ✓ Taking a messy product problem and turning it into something structured: clear UI, clean content, working systems ✓ AI integration: building custom Claude/GPT skills, evaluating agent platforms, designing LLM-powered workflows that actually save time ✓ Data analysis & ML when the problem calls for it — predictive models, clustering, dashboards, ETL pipelines ✓ Content operations: designing learning content, building review systems, managing workflows at scale ✓ UI/UX: prototyping interfaces and interactive tools using AI, iterating on design systems Tech I work with: Python, SQL, Pandas, Scikit-learn, BigQuery, Plotly Dash, Zoho, Claude Code, Lovable, Claude/GPT APIs, prompt engineering, LLM fine-tuning Good fit if you need someone who: ✓ Can own a product area, not just a task ✓ Bridges the gap between data, design, content, and engineering ✓ Ships fast using AI tools without cutting corners on quality ✓ Has edtech experience and understands learning product design

🧭 **I design and build agentic systems that survive production — observable, evaluable, and maintainable by your team after I leave.** 🏅 **Expert-Vetted | 100 % Job Success | Physics PhD, $90K+ earned. Recent: VIVIA (real-estate multi-agent platform, WhatsApp + voice + CRM) and a Neo4j-backed RAG pipeline rated ★5.0 Agents fail where teams don't look: prompt fragility, silent regressions, untraced failures, no fallback paths. That's the first thing I plan for. 🏗️ **Architectural scope I cover** - Multi-agent orchestration with LangGraph — explicit state machines, checkpointing, human-in-the-loop - GraphRAG on Neo4j — entity resolution, hybrid retrieval, explainable reasoning paths - Agent evals & observability — LangSmith / custom tracing, regression suites, cost dashboards - Production deploys — vLLM / Docker / Kubernetes, load-balanced inference, fallbacks across providers - Integration layer — WhatsApp, Twilio voice, CRM APIs, MCP servers, webhook resilience 🔬 **Background** PhD in Physics + years as a quantitative researcher. I treat agent behavior as a measurable system — I run experiments, log everything, and challenge claims that don't come with numbers. ✅ **Recent work** - **VIVIA** — Multi-agent real-estate platform: channel-agnostic core, per-agency scoping, lead follow-up sync, voice calls, CRM integration. Led modular refactor from monolith to clean separation of concerns. - **LLM/VLM fine-tuning & deployment** — custom load-balanced GPU platform, $10K+, ★5.0. - **AI Compliance system** — LLM guardrails, evaluation harness, and audit trail for regulated-industry workflows (i.e., full traceability). - **Neo4j calendar-event ingester** — production graph pipeline, ★5.0. 🛠️ **Stack** LangGraph · LangChain · LlamaIndex · Neo4j · Qdrant/Pinecone · Supabase · vLLM · FastAPI · Python/Cython/C++ · Docker · Twilio · MCP · WhatsApp/Notion SDKs If you're scoping an agent or RAG system and want someone who'll push back on the architecture before writing code — **let's talk.** 📬