Vetted Dashboard Development Professionals

Avni Tripathi

Screened ReferencesModerate rec.

Mid-level Data Scientist specializing in NLP, RAG, and information retrieval for RegTech

Gurgaon, India5y exp

“Built and deployed a production document Q&A/research platform that combines semantic search (vector DB embeddings) with structured knowledge-graph querying to reduce analyst research time. Used in high-stakes domains like Politically Exposed Person profiling and extracting critical information from ESG/regulatory documents, with a human-in-the-loop evaluation process (precision@k and source-text highlighting) to ensure accuracy.”

“Frontend/product-focused engineer who helped build Cheiron.bio from no product to production, owning major parts of an AI-powered search and document intelligence experience for bio-pharma researchers. Stands out for combining React/Next.js/TypeScript architecture depth with strong product thinking around AI workflows, citations, streaming interactions, and responsive UX in complex, data-heavy interfaces.”

“Built and productionized a real-time social-media sentiment analysis system used by a marketing team to monitor brand/campaign performance. Experienced in orchestrating LLM workflows with LangChain (validation → prompting → parsing → post-processing), plus monitoring, retraining, and RAG-style retrieval using embeddings/vector stores to keep outputs reliable over time.”

Akash Mishra

Screened

Mid-level Data Engineer specializing in ETL pipelines on GCP

Miami, Florida5y exp

“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”

Yeruva Bala Shreya Reddy

Screened

Entry Data Analyst specializing in ETL pipelines and business intelligence

Charlotte, NC0y exp

“Analytics candidate with hands-on experience building reliable healthcare reporting layers from messy transactional data using SQL and Python. Stands out for combining data transformation, KPI definition, validation rigor, and performance tuning to deliver reusable reporting assets that improve trust in operational metrics.”

Kevin Thomas

Screened

Intern Software Engineer specializing in AI, cloud, and backend systems

Torrance, CA1y exp

“Candidate has internship and graduate-project experience building AI agents, including a production log-analysis assistant using a lightweight agentic/RAG-style workflow with local GPT training and validation against historical logs. They also worked on Android/iOS game build and release processes in a Unity-based robot racing game environment, and highlight measurable LLM outcomes including 80% analysis accuracy, 2-5 second latency, and 50% cost reduction.”

Hamna Anwar

Screened

Senior Full-Stack Engineer specializing in Go backend systems

Hayward, CA8y exp

“Full-stack/backend engineer with startup-style experience spanning healthcare and B2B infrastructure SaaS. Has worked across Python, Go, and React/TypeScript, including migrating services from Node.js to Go, building microservices and dashboards, and delivering measurable API performance gains through database tuning and Redis caching.”

“Growth/marketing operator with hands-on experience across creator partnerships and performance acquisition. Sourced creators via TikTok Creator Marketplace and qualitative engagement checks, negotiated performance-based deals, and achieved a 15% CPA improvement that expanded into a long-term ambassador program. Also led persona-based GTM and funnel experiments at Haletale, driving a 20% lift in demo bookings without increasing budget.”

“Frontend-focused developer with startup/co-op experience who ships end-to-end UI features—from Figma/Canva designs to JavaScript/React implementation. Notably refactored a Bootstrap codebase to fix tablet responsiveness across every page in ~1–2 weeks, improving maintainability via semantic HTML and cleaner CSS organization. Built a React + TypeScript movie-tracking app using Firebase auth and Context-based user state, incorporating user feedback and pragmatic QA practices.”

“Frontend/mobile engineer with iOS and React/TypeScript experience who built an app (Tokidos) from proof-of-concept to production at Neuronic Works Inc. Focuses on scalable architecture (MVC/MVVM, feature-based modular structure), performance improvements (React Query, render optimization), and fast, low-risk delivery using QA scenarios and feature-flagged rollouts across web and mobile.”

“Robotics engineer who built a real, mostly self-assembled autonomous robot (WRAITH) as a final-year project, implementing ROS2-based 2D SLAM (Cartographer/SLAM Toolbox) and Nav2 on a Raspberry Pi 5 under tight CPU/RAM and OS compatibility constraints. Also delivered a full Flutter mobile control app backed by a Flask REST API (manual control, live camera streaming, mapping/navigation) and introduced an image-based verification method to improve localization.”

“Built and productionized LLM-powered workflows that generate contextual insights from structured financial data, including prompt/retrieval design, data standardization, and reliability controls like rate limiting and batching. Also diagnosed and fixed real-time failures in an automated order validation system using logs/metrics, staging reproduction, edge-case handling, retries, and alerting, while supporting sales/customer teams with demos, scripts, and FAQs to drive adoption.”

“Built and productionized an LLM-powered service desk ticket triage and reporting agent that classifies, prioritizes (including sentiment/urgency), and summarizes tickets into structured SQL outputs feeding Power BI dashboards. Emphasizes production reliability (99% uptime) with retries, schema validation, confidence thresholds, human review queues, and rule-based fallbacks, delivering 85–90% reduction in manual effort and 25–30% faster resolution times.”

“Data engineer focused on building reliable, production-grade pipelines and data services end-to-end, including a 50+ GB/day pipeline ingesting from APIs/files into Snowflake with PySpark/SQL transformations. Emphasizes strong data quality controls, monitoring/retries, and performance optimization, and has also shipped a Python data API with caching and backward-compatible versioning.”

Prasanth Kumar Korada

Screened

Mid-level QA Automation Engineer specializing in Playwright and cross-browser E2E testing

3y exp

“QA automation engineer with strong end-to-end ownership of UI automation for financial transaction workflows, using Selenium/Playwright/Cypress and CI/CD gating. Improved suite robustness via UI-API validations, negative testing, and flake reduction (intercepts + data-testid), catching critical backend calculation issues before production and cutting regression runtime by 40%.”

Iskhak Ishmakhametov

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and real-time systems

Bellevue, WA7y exp

“Full-stack product engineer with a strong real-time systems focus: built and rolled out a WebSocket-based notifications system (with robust reconnect/resync and event ordering protections) that cut update latency to under 200ms. Also owned a workflow automation platform backend in FastAPI (JWT/RBAC, versioned APIs, standardized errors), designed the PostgreSQL schema for workflows/tasks/executions, and operated deployments on AWS ECS Fargate with blue-green CI/CD and performance stabilization via caching and autoscaling.”

Habtom Desta

Screened

Mid-level Data Scientist specializing in Python, ML, and BI dashboards

Dallas, TX5y exp

“Data/NLP practitioner who builds production-oriented pipelines for unstructured text: entity extraction, topic modeling (LDA/BERTopic), and semantic search using Sentence-BERT embeddings with FAISS. Emphasizes rigorous evaluation (coherence/silhouette + manual review), entity resolution with validation, and scalable workflow orchestration using Airflow/Prefect with Spark/Dask.”

“Backend/integration-focused software engineer who built and debugged a complex location modeling system (data pipelines, APIs, optimization logic connected to a dashboard). No direct ROS/robotics experience yet, but demonstrates strong distributed-systems debugging, containerized deployment (Docker), and CI/CD/testing practices and is actively looking to pivot into robotics software.”

“Backend/data engineer focused on climate/emissions data platforms, building production Python (FastAPI) microservices and AWS serverless/ETL pipelines (Glue/Athena/Lambda/EventBridge). Demonstrated strong reliability and observability practices plus measurable optimization wins, including cutting PostgreSQL query runtimes from minutes to seconds and reducing AWS costs from ~$6k/month to ~$400/month.”

“Software engineer with demonstrated production performance wins (37% latency reduction) through SQL optimization, backend API redesign, and disciplined rollout practices (staging, feature flags). Experienced debugging distributed pipeline issues across infrastructure layers (memory pressure and network timeouts) and building AWS-based systems (Lambda + RDS) to handle request spikes, including work on a business-focused chatbot.”

Sai Vamsee Bandaru

Screened

Entry-level Data Analyst and AI Engineer specializing in machine learning and LLM systems

New York, NY1y exp

“Founding-engineer-oriented full-stack product engineer who built an AI tutor system end-to-end, spanning React UI, FastAPI backend, retrieval/LLM pipelines, and Postgres optimization. Stands out for combining product thinking with deep systems work: improving onboarding and activation, shipping quickly with beta users, and abstracting reusable retrieval infrastructure for multiple use cases.”

“Backend/ML engineering candidate focused on fintech automation who architected a zero-to-one agentic/LLM-enabled system to reconcile messy financial documents and bank transactions, reporting ~40% operational efficiency gains. Experienced migrating monoliths to event-driven microservices with incremental rollout via reverse proxy, and implementing production-grade security (OAuth2/JWT, RBAC, Supabase RLS) plus resilience patterns (timeouts/retries under concurrency).”

Gowtham Manikanta Chilukabathula

Screened

Entry-level AI and Data Analyst specializing in LLMs and analytics

Memphis, TN1y exp

“Candidate brings a blend of AI, analytics, and go-to-market support experience through an AI/data internship and graduate assistant role. They analyzed data across 50+ organizations to identify high-fit outreach segments, improving targeting efficiency by about 28%, and also built/reviewed GPT-4 and LangChain-based outbound messaging systems with strong quality controls.”