Vetted Data Visualization Professionals

“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”

“Application-layer full-stack engineer who has shipped enterprise-facing integrations and developer tooling, including an end-to-end Slack integration for automated ticket creation and a real-time feature-flag dashboard (React/TS + GraphQL/Apollo + NestJS) with audit trails. Has hands-on AWS container operations experience (ECS Fargate/ALB/RDS) and has improved product performance (35% faster dashboards) while building auth and RBAC for 500+ users.”

“AI/ML manager who has deployed production NLP in healthcare—mining unstructured clinical notes and combining them with structured patient data to predict readmissions, with strong emphasis on data alignment and terminology normalization. Also experienced operationalizing ML with Airflow/MLflow and AWS Step Functions/SageMaker, plus stakeholder-facing Power BI dashboards (e.g., marketing customer segmentation).”

“AI automation builder who shipped an OpenAI-powered weekly "trending AI tools" WoW reporting system (65 categories) that reduced a 6–7 hour manual process to ~10 minutes at negligible API cost. Also building a RAG-based content creation prompt engine that turns PDFs into storyboards with fact-checking/traceback to source lines, plus experience with AWS deployment components (Lambda, ECR, App Runner, Bedrock, API Gateway) and GitHub Actions.”

“Backend/platform engineer with payments and insurance domain experience (Cognizant), owning high-volume production systems end-to-end. Shipped a Spring Boot payment tokenization service with strong observability and phased migration that cut transaction latency ~30% and improved payment efficiency ~25%. Also productionized an ML-driven financial health/risk analytics pipeline with near real-time dashboards across 70+ schools, emphasizing interpretability, data quality, and drift monitoring.”

“Robotics/AI engineer focused on multi-agent reinforcement learning for Crazyflie drones, enabling coordination via implicit motion-based communication and a stabilizing FSM layer; reported 98.5% sim and 92% real-world behavior-recognition accuracy. Also built a modular ROS 2 wall-following system (custom nodes/services/actions) and a Raspberry Pi + OpenCV stereo-vision walking robot, emphasizing rigorous logging, stress testing, and sim-to-real deployment.”

“Full-stack engineer who builds and scales customer-facing and internal AI products end-to-end (React/TypeScript/FastAPI/MongoDB) with strong product instrumentation and rapid MVP iteration. Built an AI-powered code review assistant adopted across teams and integrated into CI/CD, reducing manual review time by 30%+, and has hands-on experience with LLM retrieval/reasoning systems (LangChain + FAISS) and microservices scaling using RabbitMQ, Docker, and AWS.”

“Backend engineer who built and scaled a zero-to-one social product backend using Supabase (Postgres, Edge Functions, Auth, Realtime) plus Neo4j for graph-based friend recommendations. Demonstrates strong production rigor: staged rollouts with metrics, incident rollback/postmortems, and complex schema refactors using expand-contract/dual-write with reconciliation and feature flags. Notably proactive about edge cases like geo-boundary realtime delivery and idempotent retry safety.”

“Robotics software engineer with hands-on ROS (ROS 1) experience building sensor-processing and state-based control pipelines in Python/C++. Demonstrated measurable reliability and performance gains in autonomous navigation—cut runtime failures by 30%, reduced replanning by 35%, and improved debugging efficiency by 40%—using timing-aware state machines, message/interface discipline, and simulation/testing with Gazebo, rosbag, Docker, and CI/CD.”

“Data scientist at Guardian Airwaves building a RAG-powered quiz generator using Grok AI, with hands-on experience solving hard document-ingestion problems (PDFs with images/tables) via unstructured.io and LlamaIndex. Has deployed production systems on AWS EC2 and brings a pragmatic approach to agent reliability (human-in-the-loop, LLM-based eval, latency/cost metrics) while effectively translating RAG concepts to non-technical stakeholders.”

“PhD researcher (University of Utah) who built a production RAG-powered Virtual Reality Research Assistant to answer lab research questions with concrete citations. Implemented an end-to-end LangChain pipeline using PyPDFLoader, chunking strategies, OpenAI embeddings, and ChromaDB, with emphasis on grounding to reduce hallucinations and ensure research-grade accuracy. Collaborated closely with a non-technical PhD advisor to scope requirements, manage cost constraints, and demo iterative progress.”

“Product-minded software engineer who owned a Shopify POS app end-to-end at Swym, shipping an MVP and then scaling iteration speed with E2E automation and CI/CD—resulting in a Shopify Badge, Top-5 App Store ranking, and +40% new user acquisition. Also built an ESG insights tool using React/TypeScript + FastAPI with Snowflake and a RAG pipeline, plus microservices patterns (async jobs, queues, DLQs, autoscaling) and internal Metabase/SQL analytics dashboards.”

“Full-stack developer who deployed a React/Node/Mongo event management app to production, focusing on secure env/credential handling and stabilizing third-party integrations (email verification, payments). Demonstrated strong cross-layer troubleshooting by isolating intermittent regional failures to load balancer/firewall misconfiguration, and has Python experience building a TF-IDF/cosine-similarity search/ranking system tailored to project requirements.”

“JavaScript engineer who effectively "maintains" an internal open-source-style React/Node.js shared library used by multiple teams—owning API stability, semantic versioning, CI/testing, logging, and documentation. Demonstrates strong cross-team debugging and change-management skills (schema-driven refactors, feature flags, validation layers) to ship new features without breaking existing workflows, plus a profiling/benchmarking-driven approach to performance.”

“Full-stack engineer with end-to-end ownership of a data-heavy financial dashboard module at Brown & Brown Insurance, spanning .NET Core APIs, EF/SQL Server, and React/TypeScript UI. Demonstrates strong focus on performance tuning (indexing, pagination, caching, async) and secure service design (Azure Key Vault, JWT/RBAC) in a microservices context.”

“Outbound-focused business development profile spanning a family-owned construction materials business in India and an early-stage startup (Jetvoy) targeting Web3/travel partners. Built ICP, messaging, and a spreadsheet-based CRM from scratch, ran multi-channel campaigns (email/LinkedIn/calls), and leveraged tools like Sales Navigator, Apollo, HubSpot/Sheets, Zapier-style automations, and ChatGPT to improve reply/meeting rates through personalization.”

“AI Engineer at DXC Technology who has shipped production LLM/NLP systems on AWS (SageMaker, FastAPI) and optimized them for real-time latency and unpredictable traffic using quantization, batching, and autoscaling. Strong MLOps and monitoring discipline (MLflow, CloudWatch, SageMaker Model Monitor) and proven business impact—delivered models with 92% predictive accuracy and cut enterprise decision-making time by 30% through close collaboration with product managers.”

“Early-career candidate with customer service experience and a cybersecurity bootcamp background (vulnerability management). Undergraduate project focused on securing online exams during COVID using identity verification (facial recognition + email/phone code) and 360-degree monitoring to reduce cheating, and they navigated student pushback to enforce integrity.”

“Full-stack engineer with healthcare/bioinformatics experience who built a real-time genomic data analysis and 2D visualization feature (React/TypeScript + D3, FastAPI) at University of Utah Health, deploying on AWS ECS Fargate with monitoring and measuring engagement via Google Analytics. Also built AWS Lambda-based ETL pipelines for lab data ingestion using pandas/NumPy with reliability patterns (idempotency, retries, CloudWatch alerting) and drove maintainability improvements through shared component libraries and React hooks.”

“Senior motion designer/creative producer with 15 years of high-end motion, video, and photography experience, including 9 years at Inovalon building enterprise brand systems. Known for translating complex healthcare journeys into polished explainer content and for scalable, modular frameworks that empower large teams (300+ employees). Also integrates generative AI (Weavy + Figma) trained on brand guidelines and original photography to maintain brand consistency at high output volume.”

“Backend engineer with deep experience modernizing a provider credentialing/compliance platform with multiple upstream/downstream integrations. Focused on building predictable, scalable REST APIs (primarily ASP.NET Core; framework-agnostic approach applicable to FastAPI), improving performance via DB/query optimization, and hardening workflows with idempotency, transactions, feature flags, and strong auth/RBAC patterns.”

“Frontend engineer/product lead with experience building a Tableau-like data visualization dashboard at StradigiAI, including a scalable SQL-like query/filter approach for high-volume data. At LogMeIn/GoTo, migrated a TypeScript React product from Redux to React Query with shared state abstractions across web, Electron, and React Native, and helped leverage a design system to support a rapid company rebrand.”

“Frontend engineer who led end-to-end development of a React-based carbon credits data collection and analysis tool, focusing on scalable architecture and performance (code splitting, SWR caching, memoization, Lighthouse monitoring). Experienced building complex route-driven TypeScript wizards with Redux/Rematch state persistence, and refactoring legacy monolithic UI into reusable, tested, documented components while shipping deadline-driven features using feature flags and tight QA collaboration.”