Vetted Data Analysts

“Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.”

“Frontend engineer with experience building real-time trading operations dashboards in React and TypeScript, focused on dense operational data, performance tuning, and maintainable component design. They have production experience optimizing large-data UIs and academic exposure to map-based weather applications using Google Maps and Mapbox, while currently requiring future H-1B sponsorship.”

“Lifelong basketball player with extensive exposure to elite Southern California high school basketball (Servite/Trinity League) and familiarity with college recruiting through close connections, who applies a structured PFF-style evaluation lens to scouting. Comfortable identifying talent via film and in-person viewing and proactively engaging prospects through social media outreach; also brings experience working demanding overnight/on-call schedules from Amazon last-mile logistics.”

“Data/analytics professional with experience across manufacturing and enterprise environments (Wisconsin School of Business project with CNH Industrial; roles/projects at Ascensia Technologies, S&C, and Adobe). Has hands-on work combining warranty/lifecycle tables with technician free-text notes using TF-IDF + tree models (XGBoost/Random Forest), and deep experience in entity resolution/reconciliation across mismatched financial systems using Python/SQL and fuzzy matching, with production-grade pipeline practices in Azure Data Factory/Databricks.”

“AppSec-focused customer advisor with hands-on experience integrating SAST/DAST/SCA into production CI/CD (Azure DevOps) and designing secure agent/scanning deployments in AWS (least-privilege IAM, private subnets, VPC endpoints). Demonstrates strong incident troubleshooting using logs/metrics/traces to diagnose load-related failures (timeouts/retry storms) and drive durable fixes, while tailoring risk/tradeoff communication across engineering, security, and leadership stakeholders.”

Praveen Nutulapati

Screened

Mid-level Generative AI Engineer specializing in LLM fine-tuning, RAG, and agentic systems

New York, NY6y exp

“Built and deployed a production multi-agent RAG system at JPMorgan Chase to automate regulated credit analysis and compliance clause discovery across large internal policy/document libraries. Implemented LangGraph-based supervisor orchestration with structured state management (Azure OpenAI) to support long-running, resumable workflows, plus hybrid retrieval + re-ranking and guardrails for reliability. Strong at evaluation/observability (trace logging, LLM-judge, HITL) and at communicating results to non-technical stakeholders via Power BI embeds and Streamlit prototypes.”

“Omnichannel paid media specialist with hands-on ownership across search, social, programmatic, CTV, TV, audio, and print, spanning both digital and traditional media. Has managed up to $750K/month in spend and cites a recent win driving a 51% lift in conversions while cutting CPA by 119% for Bookkeepers.com. Particularly strong in self-service buying, optimization, and client-facing strategic pivots across diverse industries.”

Ranfei Pang

Screened

Mid-level Software Engineer specializing in AI systems and FinTech

Boston, MA4y exp

“Amazon warehouse-tools engineer with strong full-stack and GenAI systems experience, spanning large-scale provisioning platforms and internal LLM/chatbot products. They’ve owned systems end to end, including React/TypeScript frontends, Java/AWS backend orchestration, and Bedrock-based RAG architectures, with measurable impact on latency, token cost, validation quality, and operational support load.”

Yang Sherpa

Screened

Mid-level operations and analytics professional specializing in FinTech and client delivery

New York, NY5y exp

“Operations leader with ~5 years of experience in fintech, finance, and data operations, including scaling deal execution at EquityZen during the pre-IPO secondary market boom. Stands out for building process infrastructure in fast-moving, compliance-heavy environments—creating tracking systems, CRM workflows, and onboarding playbooks that increased deal volume and cut onboarding time from weeks to days.”

“Data/ML engineer with experience across pharma (Dr. Reddy Laboratories) and financial services (Cincinnati Financial, Capital One), building production NLP and entity-resolution systems that connect messy unstructured text with enterprise SQL data. Delivered semantic search with BERT + vector DB and domain fine-tuning (reported ~35% relevance lift), and builds robust pipelines using Airflow/dbt/Spark with strong validation, monitoring, and stakeholder-aligned rollout practices.”

“Analytics-focused candidate with hands-on experience building SQL reporting tables from messy transactional and master data, plus Python workflows that automate monthly analysis and data checks. They appear strongest in KPI/reporting ownership, metric standardization, and stakeholder alignment, with examples of improving reporting consistency, surfacing issues earlier, and reducing manual reconciliation effort.”