Vetted Data Analysts in the NYC Metro

“Strategic enterprise Customer Success leader from Atlassian Cloud managing a >$10M ARR, ~33k-user account end-to-end, driving measurable adoption (+12%), services expansion (+30%), and strong satisfaction (4.5/5). Experienced leading cross-functional deployments of AI agents (Rovo) and Forge-based integrations, and translating enterprise governance needs (e.g., RBAC at scale) into roadmap-shaping product requirements.”

“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”

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.”

Priyanshu Maurya

Screened

Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics

New York, NY3y exp

“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”

“Finance data and reporting professional with PwC experience who bridges accounting and technology, especially around GL-related reconciliations, reporting accuracy, and close support. While not a direct PeopleSoft GL owner, they bring strong SQL-driven troubleshooting, ETL/data mapping remediation, and process automation experience that helped shorten close cycles and improve audit readiness.”

“Data/ML practitioner with hands-on experience building NLP systems from prototype to production: delivered a Twitter sentiment classifier with robust preprocessing, SVM modeling, and Power BI reporting, and built entity-resolution pipelines for messy multi-source customer data (reporting ~95% improvement in unique entity identification). Also implemented semantic linking/search using SBERT embeddings with FAISS vector retrieval and domain fine-tuning (reported ~15% precision lift), and applies production workflow best practices (Airflow/Prefect, Docker, Azure ML/Databricks, Great Expectations).”

“Recruiting leader who builds structured, competency-based hiring systems and can also personally run Senior Director-to-C-Suite searches. Notable for scaling a full hiring season to 175+ teacher hires and for leading a high-stakes CEO succession search, advising a board to define a new leadership vision and landing a CEO who remains successful four years later.”