Vetted Tableau Professionals

“AI/ML engineer who shipped a production blood-test report understanding and personalized supplement recommendation product, using a LangGraph multi-agent pipeline on AWS serverless with OCR via Bedrock and RAG over vetted clinical research. Also built end-to-end recommender system pipelines at ASANTe using Airflow (ingestion, embeddings/features, training, registry, batch scoring/monitoring) with KPI reporting to Tableau, with a strong focus on safety, evaluation, and measurable reliability.”

“Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).”

“Cloud/SRE-style engineer at TDS supporting revenue-critical transportation SaaS platforms on AWS/GCP with Kubernetes. Has hands-on experience leading high-impact production work including DDoS mitigation, zero-downtime MSSQL→PostgreSQL migration using CDC, and building secure GitHub Actions + ArgoCD delivery pipelines and Terraform-based GKE infrastructure.”

“Data science/AI intern at University at Buffalo Business Services who built and deployed production systems spanning classic ML and LLM assistants. Delivered real-time competitor intelligence for a Cornell-partnered, $1B beverage launch by scraping/cleaning 5,000+ SKUs and deploying models via API, then built a domain-aware LLM assistant to modernize Excel-based workflows with strong grounding, privacy controls, and sub-5s latency.”

“CTO/Chief Architect who rebuilt an IoT platform from a fragile legacy stack into an AWS-based, multi-tenant cloud-native system supporting 50k+ connected devices and 10M+ monthly events, then layered in real-time data pipelines and ML anomaly detection. Known for tightly aligning roadmaps and OKRs to business KPIs (onboarding speed, uptime, velocity) and for scaling teams into domain-focused pods; previously led a shift from LAMP to event-driven Node.js microservices using MQTT and message queues.”

“ML engineer with hands-on experience taking a Gaussian Process Regression-based intelligent survey timing system from build to real-world deployment, including a 3-week RCT on 120 participants and measurable improvements (15% response rate, 23% data quality). Also served as a key technical resource at CData for customer-facing demos and debugging hundreds of production issues, bridging engineering with Sales and Customer Success.”

“Robotics software engineer with deep ROS2 experience who owned the perception stack for an automated C. elegans manipulation system—building YOLO-based worm segmentation plus OCR label reading and integrating it into a MoveIt2 pipeline with real-time latency constraints. Also deploying ROS2 on an AgileX Tracer with ZED depth camera for vision-based person following and working on SLAM/sensor fusion, with additional production-style ML deployment experience (Dockerized FastAPI + PyTorch on AWS EC2 with CI/CD).”

“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”

“AI/ML manager who has deployed production NLP in healthcare—mining unstructured clinical notes and combining them with structured patient data to predict readmissions, with strong emphasis on data alignment and terminology normalization. Also experienced operationalizing ML with Airflow/MLflow and AWS Step Functions/SageMaker, plus stakeholder-facing Power BI dashboards (e.g., marketing customer segmentation).”

“Growth-creative and paid social marketer who runs funnel-informed creative experiments across Meta/LinkedIn (and adapts learnings to TikTok/YouTube), optimizing beyond CTR/CPL to MQL and qualified CPA. Demonstrated measurable impact by using modular creative systems, rigorous tracking (pixels + CRM events), and structured creator/editor direction to improve lead quality and downstream conversion.”

“Backend/data engineer with production experience across event-driven Python ingestion services on AWS (EventBridge/SQS/MongoDB), serverless APIs (Lambda/API Gateway), and analytics ETL (Glue → Redshift). Has modernized legacy reporting into Node.js/React systems and demonstrated measurable SQL performance wins (minutes to seconds) plus strong incident ownership with validation, DLQs, and alerting.”

“AI Engineer with production experience building an LLM-powered conversational scheduling assistant (rules-based + OpenAI GPT agents) and improving responsiveness by ~40% through architecture optimization. Strong in orchestration (Airflow), containerized deployments, and data quality (Great Expectations/PySpark), with prior work automating population health reporting pipelines (Azure Data Factory → Snowflake) and delivering insights via Tableau to non-technical stakeholders.”