Vetted Tableau Professionals

“Senior infrastructure/platform engineer with deep IBM Power/AIX (Power9, VIOS, HMC, LPAR/DLPAR) and PowerHA production ownership at scale (40 frames / ~300 LPARs), including hands-on outage recovery and performance tuning. Also delivers modern DevOps/IaC capabilities—CI/CD for Kubernetes microservices and Terraform-based multi-account AWS (EKS/VPC/IAM/RDS) with drift detection and safe rollout controls.”

“Former McKinsey consultant with MBA consulting experience who led financial/budgeting work and helped shape a nonprofit fundraising GTM strategy. Built targeted corporate outreach, tailored messaging by stakeholder, and used HubSpot-driven pipeline tracking to help secure roughly $50K in partner funding.”

Brian Sanders

Screened

Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines

Chicago, IL12y exp

“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”

“Transformation and operations leader hired by a Chief Transformation Officer to drive global process and service-experience efficiencies across North America, Europe, and Australia. Led a 25+ member cross-functional team to build a claims transformation portfolio spanning three business segments, delivering $75M in annual net benefit, and is strong in executive alignment, governance, and productivity systems (dashboards, operating cadence, operating models).”

Parth Vadera

Screened

Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps

Tracy, CA11y exp

“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”

“Customer Success Lead in healthcare AI (diabetic retinopathy screening) who owns enterprise accounts end-to-end and drives measurable adoption/retention outcomes. Experienced navigating complex stakeholder dynamics during a health system acquisition, using Tableau/Salesforce analytics and ROI storytelling to expand from pilot to full deployment, and leading cross-functional delivery of EMR-integrated SSO to unblock clinical workflow adoption.”

Tina Bai

Screened

Executive operator-founder specializing in GTM, revenue strategy, and AI-native commercial operations

New York, NY10y exp

“Operator with Deloitte consulting experience supporting PE/VC-backed portfolio companies and current experience inside a VC-funded Series C scale-up. Building a bootstrapped D2C women’s telehealth brand (Petty Pills) with two initial SKUs, deployed tech stack, and white-labeled clinical/compliance infrastructure, leveraging AI tooling to keep operations lean while focusing on full-time operator roles.”

“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”

“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”

“Seasoned business leader with decades of leadership experience (including Fortune 50/500) and prior Silicon Valley startup exposure, now pursuing entrepreneurship. Building “Datascension,” a gamified, story/episode-based career coaching platform that includes hands-on tasks (e.g., SQL queries, Python scripts) plus a participation-based credit/currency system and certification/badging, informed by feedback from recruiters and coaching/recruiting firms.”