Vetted Tableau Professionals

“Product designer at early-stage startup Pomu who combines user research, systems thinking, and hands-on implementation to shape product direction—not just screens. She helped redirect the core search experience from keyword-only to image-plus-keyword based on founder interviews, collaborated directly with ML engineering, and also codes polished front-end interactions on her own portfolio site.”

“Hands-on AI/LLM practitioner who built a RAG-based customer support chatbot and tackled production issues like data chunking complexity and response-time lag. Uses techniques such as overlapping chunks, semantic search, context engineering, and query routing, and has experience presenting technical demos/workshops to developer audiences.”

“Creator-led growth and digital marketing professional with experience as a media team lead and agency-side marketer (Furst spark), sourcing and negotiating creator partnerships for events, fintech apps, and lifestyle subscription launches. Runs data-driven, cross-platform campaigns (Instagram, TikTok, YouTube Shorts, Twitter/X) with trackable links and rapid optimization; reports doubling engagement rate in a fintech acquisition experiment and driving repeat creator collaborations.”

“Built a production RAG-based healthcare chatbot to retrieve patient medical documents spread across multiple platforms, reducing manual and error-prone searching. Implemented semantic search with custom embeddings (Hugging Face) and Pinecone, deployed via FastAPI/Docker on AWS SageMaker with MLflow tracking, and optimized fine-tuning cost using LoRA while orchestrating retraining pipelines in Airflow.”

“GenAI/LLM engineer who built and deployed a production RAG system for enterprise document search and decision support, cutting manual lookup time by 40%+. Experienced with LangChain/LangGraph agent orchestration plus Airflow/Prefect for ingestion and incremental reindexing, with a strong focus on reliability (testing, observability) and stakeholder-driven metrics.”

“Backend/platform engineer who built real-time connected-vehicle telemetry analytics at Subaru, spanning Kafka streaming, Python/FastAPI ETL, and low-latency WebSocket delivery (minutes to <2s). Strong Kubernetes + GitOps practitioner across AWS EKS and Azure AKS (Helm, ArgoCD, Jenkins/GitLab) and has led major on-prem-to-cloud migrations for financial microservices using Terraform and AWS DMS with measurable cost and reliability gains.”

“Lifecycle/CRM marketer who built financing-journey email campaigns at Blue X Trade using Mailchimp and n8n, including an AI agent to validate user info and trigger instant correction emails—improving retention and ROI. Runs structured A/B tests on dynamic personalization (name/location/trading country) that increased engagement and bookings, and has led cross-functional promotions while managing third-party rewards integration issues with monday.com.”

“Built and deployed a production AI “term explainer” agent that adapts explanations to beginner/intermediate/expert users by combining multi-step LLM reasoning with grounded Wikipedia retrieval. Owns end-to-end agent orchestration (smolagents/Python), reliability patterns (fallback across LLM providers, retries, guardrails), and observability/metrics-driven evaluation; also partnered with a non-technical researcher to deliver a plain-language research assistant agent.”

“CRM/lifecycle marketer with experience reactivating inactive members in a gaming/loyalty context, using RFM-style segmentation and multi-channel journeys (email plus host phone outreach). Demonstrated measurable lift (20% reactivation/engagement) and optimization through A/B testing of incentive strategy, while coordinating closely with Creative, Operations, and Compliance during major campaigns.”

“LLM/MLOps engineer who has shipped a production RAG-based technical documentation assistant (FastAPI) cutting manual review by 45%, with deep hands-on retrieval optimization in Pinecone/LangChain (HNSW, hybrid + multi-query search, caching). Also brings healthcare domain experience—building Airflow-orchestrated EHR pipelines and delivering FDA-auditability-friendly predictive maintenance solutions using SHAP/LIME explainability surfaced in Power BI.”

“ML/LLM engineer with production experience building a compliant RAG-based virtual assistant at Intuit, optimizing embeddings and FAISS retrieval (including PCA) for low-latency, privacy-controlled search and deploying via AWS SageMaker containers. Also built scalable Airflow+MLflow pipelines using Docker and KubernetesExecutor, cutting training cycles by 37%, and partnered with civil engineers/project managers at Aegis Infra to deliver predictive maintenance for construction equipment.”

“Backend/data engineer who builds Python (FastAPI) data-processing API services for internal analytics/reporting, emphasizing modular architecture, async performance tuning, and reliability patterns (health checks, retries, observability). Also migrated legacy on-prem ETL pipelines to Azure using ADF/Data Lake/Functions and implemented a near-real-time ingestion flow with Event Hubs plus watermarking to handle late events and deduplication.”

“AI Engineer Co-Op at Northeastern University who built a production Patient Persona Chat Bot to help nursing students practice clinical interactions, fine-tuning Llama 3 and integrating a LangChain + Pinecone RAG pipeline deployed on Amazon Bedrock. Emphasizes clinical accuracy and reliability with guardrails, retrieval filtering, and continuous evaluation, and also brings strong data engineering/orchestration experience (Airflow, EMR/PySpark, ADF, dbt, Databricks, Snowflake).”

“LLM/GenAI engineer who built a production AI-powered credit risk policy summarization and compliance alerting platform at HCL Tech, focused on factual accuracy and auditability for a financial client. Implemented a multi-retriever LangChain RAG architecture with citations-only prompting, fallback agents, and human-in-the-loop legal review—cutting manual review time by 35% and scaling to 12 teams.”

“AI/NLP-focused practitioner who built a zero-/few-shot LLM event extraction system on the long-tail Maven dataset, combining prompt-structured outputs with LoRA/QLoRA fine-tuning and rigorous F1 evaluation. Also implemented entity resolution/data cleaning pipelines and embedding-based semantic search using Sentence-BERT + FAISS, and has healthcare experience delivering a multilingual speech/translation mobile prototype using HIPAA-compliant Azure Cognitive Services.”

“Senior Business Strategist (Robotproof) who effectively operated in a Chief-of-Staff-like capacity for both internal executives and Samsung’s President/CMO/Head of Strategy, running multi-workstream initiatives across strategy, marketing, and VR product/engineering. Built KPI/OKR dashboards and executive briefing rhythms to accelerate decisions and delivered an 8% sales lift via a targeted regional strategy pilot that included localized assets, an incentivized sales program, and a bespoke VR training tool.”

“LLM engineer who built a production-style educational questionnaire generation system (MCQs/fill-in-the-blanks/short answers) using Hugging Face models (BERT/T5) and implemented grounding, decoding tuning, and post-generation validation to control hallucinations and quality. Also developed a "tech care" assistant chatbot with a custom Python orchestration/router layer (intent classification, context management, multi-step flows) and a structured testing/evaluation approach including expert review and automated checks.”

“Transportation procurement/sourcing professional with experience leading carrier RFP evaluations and onboarding decisions against cost-per-load targets. Leverages freight market indicators (notably the Cass Freight Index) and spreadsheet-based analysis to forecast demand and shape contracting/volume strategy, and has contributed to route-optimization process improvements that increased delivery efficiency and receiving-yard satisfaction.”

“Production infrastructure engineer from Textron Systems who owned IBM Power/AIX 7.2 environments supporting manufacturing-critical automated RF test workloads. Deep hands-on experience with VIOS/HMC, DLPAR performance issues, SAN/vFC failures and failover recovery, plus modern DevOps practices (Azure DevOps CI/CD, Key Vault) and Terraform-based AWS infrastructure with remote state/locking and drift controls.”

“Enterprise healthcare SaaS implementation and customer success leader focused on OR/clinic scheduling optimization, owning end-to-end deployments from discovery through training, adoption, and renewal across multi-hospital systems. Strong analytics/ROI storytelling (Tableau/Looker, QBRs) linking AI-driven outreach and block release workflows to increased case volume and improved block utilization, and experienced partnering with Product/Sales to resolve integrations and drive roadmap/upsell outcomes.”

Vidit Naik

Screened

Junior AI/ML & Full-Stack Engineer specializing in LLMs and RAG systems

San Francisco, CA2y exp

“Forward-deployed engineer who built a production AI drone-control chatbot that lets users fly a drone via natural language while viewing a real-time feed. Implemented RAG over drone SDK documentation (vector DB + top-k retrieval) and LoRA fine-tuning, with a focus on latency, token efficiency, and cost reduction, and regularly works with non-technical clients to integrate and explain AI system architecture.”

Santhoshi Priya Sunchu

Screened

Mid-level Data Scientist specializing in NLP and predictive modeling

Massachusetts, USA5y exp

“AI/ML practitioner in healthcare/insurance (Blue Cross Blue Shield) who built and deployed a production NLP system to classify patient risk from unstructured clinical notes. Experienced in end-to-end pipeline orchestration (Airflow, AWS Step Functions/Lambda/SageMaker) and real-time optimization (BERT to DistilBERT on AWS GPUs), with strong clinician collaboration to drive adoption.”

Jitesh Kumar S

Screened

Junior Machine Learning Engineer specializing in NLP, computer vision, and MLOps

Lafayette, IN3y exp

“ML/LLM engineer with Meta experience building production AI systems for near real-time user-report classification and summarization under strict latency (<250ms), safety, cost, and privacy constraints. Has hands-on MLOps/orchestration experience (Airflow, Spark, MLflow, Kubernetes, Docker, GitHub Actions) plus observability (Prometheus/Grafana) and applies rigorous evaluation, staged rollouts, and A/B testing to keep agent workflows reliable in production.”

Asanti Mokwala

Screened

Junior Data & Insights Analyst specializing in BI, dashboards, and automation

Remote3y exp

“Worked on taking an LLM-based system at Soundmakr from prototype to production by adding prompt constraints, validation/guardrails, deterministic ranking, and robust logging/monitoring with feedback loops. Also partnered with product/marketing during an internship on Thea: Study Smart to analyze onboarding drop-offs and run A/B tests on AI-driven flows, translating results into actions that improved retention and conversion.”