Data scientist based in Jersey City, NJ · Working in New York City (NYC)
Summary
I operate at the crossroads of data science and software engineering, coordinating the development of Firmwide systems across multidisciplinary teams. With expertise in AI strategy, cloud infrastructure, and emerging technology, I leverage organizational data to inform strategic decisions that align leaders with their people to create a safer and more productive environment.
Work Experience
Data Science Specialist, McKinsey & Company
Jan 2024 – Current
New York City, NY
Architecting agentic AI systems with multi-step orchestration, tool-use design, and autonomous task execution, balancing AI autonomy with human oversight through agent guardrails and feedback mechanisms.
Implementing LLM evaluation frameworks with PromptFoo, building CI/CD pipelines and dashboards for organization-wide red teaming, quality assurance, and democratized NLP through RAG.
Designing deep learning architectures for novel Stochastic and Ordinal Differential Equation methods in Diffusion and Flow Matching, with custom FIDNet models for evaluating generative AI output.
Owning full-stack workstreams across Python, Node.js, and AWS to ship agent-powered pipelines at Firm scale, from knowledge asset creation to structured content workflows.
Defined a taxonomy of skills for recruitment, staffing, and analytics by constructing a knowledge graph leveraged by downstream services and teams.
Senior Data Scientist, McKinsey & Company
Dec 2021 – Dec 2023
New York City, NY
Designed topic modeling methods for millions of complex text documents over various data sources annually, including a weekly pulse to capture emerging topics and issues across the Firm.
Enabled faster cross-team development with CI/CD pipelines in GitHub Actions and AWS CloudFormation, mitigating risk across our data and deployment layers.
Led team deep-dives to implement new packages and papers, helped design the interview process, conducted interviews, and mentored two junior colleagues receiving promotions within a year of joining.
Data Scientist, McKinsey & Company
May 2019 – Dec 2021
New York City, NY
Developed production-grade ML analytic pipelines in Kedro that outperformed vendor model, saving the Firm over a million dollars annually.
Transitioned our team’s models to scalable AWS infrastructure, scaling to meet demand over 1.2 million times annually without error.
Increased explainability of highly sensitive model inferences across the people space to improve decision-making impact.