Vetted Data & Analytics Professionals

“Backend-focused engineer with experience at Ramp, Easebuzz, and George Mason University, spanning data pipelines, workflow automation, and production reliability. Stands out for quantifiable performance gains, strong debugging instincts in distributed job systems, and translating ambiguous finance operations processes into measurable automation outcomes.”

Abhishek Ghaisas

Screened

Intern-level Data Scientist specializing in AI and full-stack applications

Pune, India1y exp

“Engineer with hands-on experience building production ML and Python backend systems, including a real-time social media monitoring pipeline handling 1000+ events per second and a prototype AI operations assistant for Seattle-Tacoma Airport. Stands out for combining reliability engineering, automation, and LLM/NLP-to-SQL work, with measurable impact such as improving uptime from 92% to 99.4%.”

“Built and deployed “ApartmentFinder AI,” a multi-agent system using Google ADK, Gemini, and Google Maps MCP to automate apartment shortlisting and commute-time analysis, cutting a 45–70 minute user workflow down to ~30 seconds. Also has strong delivery/process chops from serving as an SDLC Release Coordinator, managing 52+ releases and reducing SDLC issues by 84%.”

“At Provenbase, built and shipped a production LLM-powered semantic search and candidate matching platform (RAG with GPT-4/Gemini, multi-agent orchestration, Elasticsearch vector search) to scale sourcing across 10M+ candidate records and 1000+ data sources. Drove sub-second performance, cut LLM spend 30% with routing/caching, and improved recruiting outcomes (+45% sourcing accuracy; +38% visibility of underrepresented talent) through bias-aware ranking and tight collaboration with recruiting stakeholders.”

“Data engineer who has owned high-volume production pipelines end-to-end (200–300 GB/day) on AWS, implementing strong data quality/observability and achieving 99.9% reliability while cutting data issues ~33%. Also built a large-scale external data collection system ingesting millions of records/day with anti-bot/rate-limit handling and backfill tooling, and shipped a versioned REST service exposing curated Snowflake data to downstream teams.”

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-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.”

“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.”