Vetted pandas Professionals

“Serial founder and fractional CTO with 8 companies founded and 3 exits, now looking to commit full-time to a venture-backable startup. Currently advising two startups that recently raised $400K friends-and-family and $1M pre-seed, and brings thoughtful perspective on venture-scale economics, team quality, and AI disruption risk.”

Yanet Fernandez

Screened

Junior Data Analyst specializing in healthcare analytics

Fort Myers, FL2y exp

“Analytics/data professional with hands-on experience turning messy semi-structured CRM JSON data in Snowflake into clean reporting layers using SQL and validation logic. Brings a practical mix of data engineering, Python automation, metric design, and stakeholder alignment to improve reporting accuracy and speed of decision-making.”

“Current data analyst intern at Across and MBA student who combines SQL, Python, and visualization skills across both workplace and academic analytics projects. Has hands-on experience cleaning messy customer service and time-tracking data for payroll-related analysis, plus building sentiment and trend-based analyses in Python and dashboards for stakeholder communication.”

“Analytics professional with hands-on experience turning messy CRM and campaign data into standardized reporting datasets using SQL and Python. At EcoSolutions/EcoServices, they built reusable KPI pipelines, dashboards, and metric definitions that reduced manual reporting and improved time to conversion by roughly 55% through better segmentation and campaign optimization.”

“Analytics-focused candidate with hands-on experience building SQL and Python pipelines for messy, high-volume data across e-commerce, marketing, healthcare, and regional resource allocation use cases. Particularly strong in turning ambiguous business problems into operational metrics and trusted Power BI reporting, including CLV, patient retention, and vulnerability-based segmentation.”

“Junior web developer turned applied AI builder who has shipped both user-facing web UX improvements (Vue.js + Drupal/Twig) and production LLM systems. Built a Google Cloud-hosted Llama/Ollama RAG customer-service chatbot with citation-based guardrails and a metrics-driven eval loop, and also delivered a large-scale Python pipeline analyzing 14M Amazon consumer reviews for flavor-trend detection.”

“Analytics-focused candidate with hands-on experience building compliance and contract utilization reporting from messy contract, vendor, subcontractor, and payment data. They combine SQL and Python automation to improve reporting speed and accuracy, and show strong stakeholder discipline through validation sessions, documentation, and dashboard adoption.”

RAUNAQ BEDI

Screened

Entry-level Software Engineer specializing in AI, data engineering, and cloud DevOps

San Francisco, CA1y exp

“Product-minded full-stack engineer with strong React/TypeScript, serverless AWS, and Postgres depth, highlighted by owning real-time personalization and onboarding experiences at mParticle. Stands out for combining deep performance debugging with measurable product impact—improving activation by 28%, reducing time-to-insights by 35%, and building reusable internal platform primitives adopted by 12 teams.”

“Full-stack developer building Lynx Cafe, a React Native/Expo iOS app for coffee shop customer feedback, while using AI and multi-agent workflows to accelerate scaffolding, architecture, and backend migration. Stands out for treating AI like a junior engineering team—assigning specialized tasks, manually integrating outputs, and enforcing code quality, security, and architectural consistency.”

“Graduate-level candidate who uses AI as a disciplined engineering assistant rather than an autonomous replacement, with hands-on experience coordinating manual multi-agent coding workflows across planning, implementation, and testing. They emphasize scoped execution, clear constraints, and human ownership of final merges, suggesting a thoughtful and practical approach to AI-augmented software development.”

“ML engineer with hands-on experience building production AI systems spanning agentic AI, RAG, LLM automation, fraud detection, and predictive analytics. At Origami Risk, they designed and implemented an enterprise RAG platform end to end using LangChain, LangGraph, vector search, and AWS Bedrock to improve internal knowledge retrieval, reduce manual effort, and raise response quality across teams.”

“Software engineer at Expedera working at the intersection of deep learning compilers and neural processor hardware, focused on making customer models run efficiently across custom HW architectures. Particularly notable for building a zero-to-one multi-chip scheduler in a Python + C++ stack and for translating complex model optimization problems into customer-facing performance gains for hardware deployments, including autonomous driving use cases.”