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Vetted Data Scientists in the NYC Metro
Pre-screened and vetted in the NYC Metro.
Christopher Sipola
Senior Machine Learning Engineer specializing in LLMs and recommendation systems
“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”
Franklin Dickinson
Senior Data Scientist specializing in product analytics and applied AI
“Product data scientist at Meta who also built Fogo, a personal finance app, as a solo developer with a React/FastAPI/Postgres stack and sophisticated LLM evaluation infrastructure. Particularly strong in AI backend quality systems, experimentation, and production decision-making around model cost, latency, and reliability.”
Senior Data Scientist / ML Engineer specializing in LLMs, generative AI, and MLOps
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps
Mid-level Data Scientist specializing in ML for healthcare and strategy analytics
Alexander Choy
Director of AI/ML Engineering specializing in MLOps, data platforms, and 3D computer vision
“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”
Senior Data Scientist specializing in GenAI and LLM systems for financial services
Staff-level Software Engineer specializing in AI, data platforms, and cloud infrastructure
Mid-level Data Scientist / ML Engineer specializing in NLP, recommender systems, and insurance analytics
Mid-level Data Scientist specializing in GenAI, NLP, and deep learning
Mid-level Data Scientist specializing in GenAI, NLP, and deep learning
Senior Software Engineer specializing in AI infrastructure and distributed systems
Abhay Murjani
Director-level Data Science Manager specializing in ML forecasting, experimentation, and MLOps
“Data/ML engineer with experience at American Express and Amazon, owning an end-to-end rewards redemption/liability ML pipeline (~200GB) with rigorous regulatory/audit validation and quarterly executive reporting. Also built web-scraped product datasets with anti-bot protections at a startup and helped modernize an authn/authz service using AWS, plus led early-stage migration work from an internal warehouse to GCP with CI/CD and cloud observability.”
Executive CTO and AI leader specializing in enterprise SaaS and generative AI
Mid-level Data Scientist specializing in global health and clinical decision support
Senior Data Scientist specializing in LLM products, voice agents, and FinTech risk modeling
Principal Machine Learning Architect specializing in AI platforms and data science
Praveen Nutulapati
Mid-level Generative AI Engineer specializing in LLM fine-tuning, RAG, and agentic systems
“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.”
YASH JADHAV
Junior Data Scientist specializing in customer and growth analytics
“Candidate combines fraud analytics experience at Citi with a clinical AI capstone involving reproducible ML pipelines for imaging and notes data. They stand out for turning messy, high-volume data into decision-ready reporting, automating evaluation workflows, and translating analytics into operational impact—from fraud rule changes to retention metric adoption.”
Mid-level Data Scientist specializing in financial risk, fraud detection, and GenAI NLP
Mid-level Data Scientist specializing in NLP, GenAI, and time-series modeling
Senior Data Scientist specializing in LLMs, Agentic AI, and MLOps
Priyanshu Maurya
Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics
“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.”