Vetted Tableau Professionals

“Merchandising/sourcing professional from World Market with deep experience building and optimizing home/fashion partnerships end-to-end—using tariff-driven margin pressure to shift sourcing outside China while maintaining design elevation. Highly metrics-driven across OTB, SKU productivity, margin/IMU, full-price sell-through, attachment rate, and digital conversion, and comfortable managing 50+ vendor negotiations simultaneously.”

“ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.”

“Creative director/designer spanning high-polish marketing brand work and enterprise innovation: built a full podcast brand ecosystem and a cinematic historical visualization using Google Veo 3. Also led an AR/VR-assisted remote troubleshooting initiative at TriMas (HoloLens-style workflows), delivering a 40% MTTR reduction and cutting expert travel by 50%+ while standardizing reusable interaction components for global teams.”

“AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.”

Steven Zavala

Screened ReferencesStrong rec.

Director-level growth marketer specializing in DTC e-commerce and CPG

Los Angeles, CA10y exp

“Lifecycle/CRM marketing leader from the wine and beverage space who has owned high-volume email/SMS programs end-to-end and translated CRM insights into broader revenue strategy. Stands out for combining rigorous process design, cross-channel automation, and personalization testing to drive measurable gains, including a 45% lift in incremental email revenue and $1.6M in incremental on-site upsell/cross-sell revenue.”

“Performance marketer managing a $500K/month paid media portfolio across Google, Microsoft, Meta, TikTok, Reddit, YouTube, and Quora with a focus on profitable growth. Uses a rigorous testing framework across creatives, bidding, and landing pages (leveraging Adobe Analytics and customer journey dashboards) and cites 200–400% YoY revenue growth plus 200–300% ROAS improvement; recently restored 20–30% of lost conversions at Labcorp within two weeks after diagnosing competitive and seasonal shifts.”

Rachel Downey

Screened ReferencesStrong rec.

Mid-Level Game Designer specializing in systems and economy design

Livermore, California4y exp

“Game economy/progression designer with hands-on ownership of end-to-end systems and live-ops tuning on major mobile titles (Star Trek Fleet Command, Marvel Contest of Champions). Builds spreadsheet-based simulations and telemetry-driven tuning loops to prevent inflation and reduce progression friction, including a multi-iteration optimization that lifted D7 retention ~7% while maintaining monetization targets.”

“Startup operator with experience spanning Series D scale-up GTM strategy at Motive and earlier-stage marketplace operations at Fleek and BridgeLinx. Stands out for building operating infrastructure, redesigning sales compensation, and automating leadership reporting with measurable impact, including 12% sales efficiency gains, 40% less reporting overhead, and 9% better rep performance.”

“ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).”

“Built and deployed a GPT-4-powered medical assistant for clinical staff to reduce time spent searching guidelines and EHR information, with a strong emphasis on safety and compliance. Uses strict RAG, confidence thresholds, and fallback behaviors to prevent hallucinations, and runs production-grade workflows orchestrated with LangChain/LangGraph plus Docker/Kubernetes/MLflow and monitoring for reliability and cost.”

“LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.”

“LLM/agentic workflow specialist with healthcare deployment experience who has taken LLM-based automation from prototype to production using operator-in-the-loop validation, RAG-style retrieval, RBAC, and monitoring for sensitive data compliance. Demonstrated real-time incident resolution (retrieval timeouts due to network/proxy misconfig) and strong GTM support—hands-on developer workshops and sales demos translating technical safeguards and real-time ETL into measurable ROI (70% ops reduction, ~$200K/year savings).”

“LLM/agentic systems practitioner focused on taking customer prototypes to production by hardening reliability (APIs, monitoring, security) and adding guardrails, evals, and incremental rollouts. Experienced diagnosing RAG/agent failures via structured tracing and fixing retrieval-quality issues (freshness checks, filters, schema enforcement). Also supports pre-sales by leading developer demos/workshops and building targeted POCs to address scalability/reliability objections and drive adoption.”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Built a production RAG-based “unified assistant” that consolidates siloed company documents into a single chatbot while enforcing fine-grained access control via RBAC/metadata filtering with OAuth2/JWT. Experienced orchestrating LLM workflows with LangChain/LangGraph + FastAPI (async + caching) and measuring performance via retrieval accuracy and response-time SLAs. Also delivered a churn analytics solution with dashboards and automated retention campaigns using n8n.”

“Built and deployed a production RAG-based document Q&A system on Azure OpenAI to help business teams search thousands of PDFs/Word files, using Qdrant vector search, MongoDB, and a Flask API. Demonstrates strong production engineering (streaming large-file ingestion, parallel preprocessing, monitoring/retries) plus systematic prompt/embedding/chunking experimentation to improve accuracy and reduce hallucinations, and has hands-on orchestration experience with ADF/Airflow/Databricks/Synapse.”

“ML/NLP engineer who built a RAG-based technical assistant for Caterpillar field engineers, transforming PDF keyword search into intent-based semantic retrieval across manuals, logs, sensor reports, and technician notes. Strong in productionizing data/ML systems (Airflow, PySpark) with rigorous preprocessing, entity resolution, and evaluation—delivering measurable gains in accuracy, relevance, and duplicate reduction.”

“Customer-support/engineering background spanning Informatica PowerCenter ETL and IBM demos/workshops, with hands-on experience hardening data workflows for production (error tables/reject links, validation, restart strategies, alerting, performance tuning). Also demonstrates a clear, systems-level approach to diagnosing LLM/agentic workflow issues (prompt/RAG/tooling/memory) using instrumentation and iterative fixes, and has partnered with sales on POCs by defining success metrics and mapping solutions to customer architectures.”

“Operated as a data-driven cross-functional leader during a major company transition, owning initiatives across sales forecasting, pipeline analytics, and GTM process changes. Built an executive operating cadence with dashboards and weekly briefing packets that reduced information-chasing and improved decision-making, and successfully mediated Sales/Finance forecast assumption disputes using a single-page, fact-based recommendation.”