Vetted Data Visualization Professionals

“Built a demo-live LangGraph/LangSmith LLM agent that translates natural language into SQL against a self-built MLB statistics database, using a vector-store knowledge base of example queries. Focused on predictable orchestration via conditional nodes, YAML-driven behaviors, and tool-gated function calling, with testing via LangSmith and Python scripts.”

“Built and launched “Language AI,” a Next.js/TypeScript app that clones a user’s voice (via ElevenLabs) to deliver language lessons in their own voice, using Supabase for auth/Postgres/storage and hosting backend on Render. Post-launch, identified ElevenLabs voice-clone limits after initial users and reworked the pipeline to store audio assets and delete clones to support more concurrent users; also added Google auth to improve adoption. Previously worked in a high-growth startup environment (Study Park) taking concepts from ideation to production.”

Nicholas Huang

Screened

Mid-level Full-Stack Developer specializing in FinTech web applications

Cincinnati, OH6y exp

“Front-end engineer experienced modernizing legacy React/TypeScript applications, including building a highly customized navigation system controlled by feature flags and documenting it for cross-team adoption. Demonstrates strong performance optimization skills (profiling, provider refactors, memoization) and deep debugging ability, including resolving UI jank traced to Reach Router’s accessibility-driven focus behavior.”

Mohith Venkata

Screened

Mid-level Full-Stack Developer specializing in cloud-native APIs and data workflows

Tukwila, WA4y exp

“Built and owned end-to-end ordering and inventory/order management systems for a wholesale distributor, delivering an MVP quickly and iterating based on direct observation of daily users. Experienced with TypeScript/React + Node.js layered architectures and microservices using RabbitMQ, including real-world scaling issues (duplicates, backpressure) and observability practices (correlation IDs, structured logging).”

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.”

Surya Danturty

Screened

Intern AI/ML Engineer specializing in computer vision and time-series forecasting

Riverside, CA0y exp

“Undergrad who built a production RAG chatbot for a messy college website using OpenAI embeddings + FAISS, overcoming hard-to-crawl/non-selectable site content and strict API budget limits. Applies information-retrieval best practices (section-based chunking with overlap, precision/recall evaluation) and reliability techniques (edge-case testing, similarity thresholds, fallback responses), and has experience scaling similar indexing work to ~300,000 Wikipedia pages.”

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.”

Shabari Vignesh

Screened

Mid-level Data Engineer specializing in cloud data platforms and AI agents

Santa Clara, CA6y exp

“Data/Backend engineer who has owned end-to-end merchant analytics systems on AWS: orchestrated multi-source ingestion (FISERV/Shopify/Clover) with Step Functions/Lambda, enforced strong data quality gates, and served curated datasets via Redshift and a FastAPI layer. Also built an early-stage Merchant Insights AI agent that converts natural language questions into SQL using OpenAI models, with full CI/CD and observability.”

Farida Poor

Screened

Junior Machine Learning Engineer specializing in NLP and multimodal transformers

Bay Area, CA3y exp

“Built and deployed LLM-powered agentic chatbot and text-to-SQL systems using LangGraph/LangChain (and Bedrock), structuring workflows as DAGs with planning/replanning and validation to improve tool-calling reliability and reduce hallucinations. Operates production feedback loops with online/offline metrics, drift detection, and LangSmith-based evaluation pipelines, and regularly partners with business stakeholders and clinicians using slide decks and visual charts.”

“Outbound-focused SaaS seller with a track record of creating pipeline in ambiguous/early-stage environments and closing complex deals. Notably sourced a New Zealand opportunity via LinkedIn, convinced the account to reopen a closed RFP, ran demos/POC, and closed a $1.8M deal over ~7 months; also experienced in security/legal redlines and multi-stakeholder consensus building (including winning over a resistant VP of IT).”

David Alvarado

Screened

Junior Business Analyst specializing in data analytics and BI

Orlando, FL3y exp

“Analytics candidate with insurance domain experience at Chubb, combining strong SQL/Python data engineering for claims reporting with business-facing metric design in Power BI. Also built an MLB game outcome predictor that beat Vegas implied probabilities using public data, showing strong product thinking and applied modeling ability beyond standard BI work.”

“Backend-focused engineer with hands-on experience deploying AI-driven document processing and RAG-based workflows using Python, LangChain, FAISS, and REST APIs. Has owned projects from requirements through post-launch monitoring, including debugging production retrieval issues and building reliable pipelines for messy PDFs/scans and compliance-oriented document analysis.”

“Lifecycle/CRM marketer with hands-on and strategic experience in fintech membership products at MoneyLion, spanning onboarding, activation, retention, and win-back across email, push, and in-app. Brings strong Iterable and Hightouch execution skills plus prior people management experience from Sync AI, making them a blend of operator, strategist, and team lead.”

“Senior full-stack engineer with startup experience building multi-tenant B2B SaaS platforms for manufacturing and financial operations. Strongest in Python back-end development and React/TypeScript front ends, with hands-on AWS microservices, enterprise integrations like Siemens, and measurable performance gains including a 30% reduction in application load times.”

Nannalin Ongprasert

Screened

Senior Software Engineer specializing in frontend platforms and partner integrations

San Francisco, CA10y exp

“Frontend/product engineer with 9.5 years at HouseCanary building real estate data products across consumer and enterprise surfaces. They describe owning features end-to-end—from product shaping and API design to React/TypeScript architecture and deployment—including homeowner renovation calculators and real-time enterprise report-generation workflows.”

“Frontend-leaning full-stack product engineer with experience in insurance and financial analytics, combining UI design, React/TypeScript implementation, and backend integration. Stands out for shipping data-heavy dashboards, real-time collaborative features, and early generative AI document-analysis workflows using Spring Boot, LangChain, and AWS Bedrock.”

“Healthcare product leader focused on regulated analytics platforms for hospitals, health systems, and payers. They combine deep CMS/HIPAA domain expertise with hands-on product strategy, cloud/data architecture collaboration, and AI prototyping—highlighted by improving CMS-aligned readmission prediction accuracy to within 3% and leading a CloudQI-based quality logic transformation.”

“Marketing/visual designer with government/energy experience, including leading DOE infographic work translating highly technical industrial decarbonization content into clear, accessible narratives. Builds scalable template systems (infographics and InDesign fact sheets) for high-volume output, and produces social video content using Adobe Express with custom Illustrator iconography and Adobe Stock backgrounds.”

“UE5 Blueprint-focused gameplay/system designer who shipped an XR interactive experience (“Echoes of the Moon”), owning interaction logic, progression triggers, state management, and animation syncing through ship. Emphasizes modular component-based architecture with interfaces and data-table-driven tuning, plus strong profiling/optimization skills (refactoring Tick-heavy systems to event-driven) validated through 20–30 user playtests and mobile XR (Android) frame-budget constraints.”

“Backend engineer with health-tech AI platform experience who designed a modular FastAPI/PostgreSQL architecture supporting real-time user data and swap-in AI workflows. Has hands-on production experience with observability (CloudWatch, structured logging, LangSmith/LangGraph/LangChain tracing), secure auth (OAuth2/JWT, RBAC, RLS), and careful data-pipeline migrations using parallel runs and rollback planning.”

“Full-stack engineer with experience building customer-facing fintech mobile features end-to-end (loan estimate comparison) and scaling event-driven microservices in enterprise environments (Verizon). Has designed TypeScript/React/Node systems with queues/caching and built an internal rule-engine for bulk Excel ingestion that reduced data errors and manual rework through automated validation.”

“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”

“Built a production LLM-RAG system at McKesson to let internal healthcare operations teams query large volumes of unstructured operational documents via natural language with source-backed answers, designed with HIPAA/FHIR compliance in mind. Demonstrated strong production engineering across hallucination mitigation, retrieval quality tuning, and latency/scalability optimization, using LangChain/LangGraph and Airflow plus rigorous evaluation/monitoring practices.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”