Vetted Tableau Professionals

“Salesforce-focused engineer with hands-on depth across Service Cloud, OmniScript/DataRaptor, LWC, Aura, and Apex. Particularly strong in building metadata-driven workflows that let operations teams change intake flows without developer tickets, while still making disciplined architecture decisions around when custom code is actually warranted.”

“Lifecycle/CRM marketer with experience at Fandango and Young & Reckless, owning high-volume multi-brand campaign calendars and building Braze-based email/SMS/push journeys. Stands out for tying lifecycle strategy to measurable business impact, including 14% lift in email-attributed revenue, 18% CLTV improvement, and 22% higher activation through behavior-based experimentation.”

“AI/LLM-focused builder with internship experience at Curated, where they owned a voice AI support deployment end-to-end and built a RAG-based internal knowledge assistant. They pair practical production instincts with measurable outcomes, including a 30% reduction in human-handled support tickets, a 20-point NPS improvement, and a 40% reduction in manual document search across five teams.”

“Healthcare analytics candidate with hands-on experience turning messy claims and clinical data into validated SQL/Python pipelines and Power BI dashboards. They have delivered measurable impact in revenue cycle operations, including 15-18% improvement in reimbursement accuracy and 40-45% reduction in manual reporting effort.”

“Data science and AI professional with Capital One experience building churn prediction and GenAI-powered document intelligence solutions. Stands out for pairing hands-on technical depth in NLP, LLMs, and analytics with strong business communication, including driving adoption across teams and contributing to a 25% reduction in customer churn.”

“Built and deployed an LLM-powered customer support assistant (“Notable Assistant”) focused on automating common post-customer queries while maintaining multi-turn context and meeting scalability/latency needs. Experienced with production orchestration and operations using Kubernetes and Apache Airflow (DAG-based ETL, scheduling, monitoring/alerts), and has partnered closely with customer service stakeholders to align chatbot behavior with brand voice through iterative testing.”

“Applied NLP/ML engineer with experience at KeyBank and Novartis building production document intelligence and entity-resolution systems in finance and healthcare. Has delivered end-to-end pipelines (Airflow + AWS) using transformers (DistilBERT/Sentence-BERT), vector search (FAISS/Milvus/Pinecone), and human-in-the-loop labeling to achieve measurable gains (40%+ faster queries; up to 88% F1 and 93% precision/90% recall in entity linking).”

Janvitha Mandyam

Screened

Mid-level AI/ML Engineer specializing in Generative AI and NLP

Chicago, IL4y exp

“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”

Andrew Sheehan

Screened

Executive engineering leader specializing in enterprise architecture and digital transformation

27y exp

“Candidate has spent years working with startups across various industries and has been involved in multiple stages of company building, including hiring, technology choices, and budgeting. They appear especially oriented toward operational discipline, cost control, and evaluating ideas through structured cost, time, and value analysis.”

“GenAI/RAG engineer who has deployed a production policy/regulatory search assistant for a financial client using LangChain + Vertex AI, FastAPI, Docker/Kubernetes, and Airflow-orchestrated data pipelines. Demonstrated measurable impact with 50–60% latency reduction and 70% fewer pipeline failures, plus KPI-driven grounding evaluation (90%+ target) and strong cross-functional collaboration with compliance/business teams.”