Expert Details
Machine Learning & AI Engineering, Fraud Detection & Payment Intelligence Systems, Search & Recommendation Systems, Large Language Models (LLMs)
ID: 740755
New York, USA
Expert currently leads a large machine learning engineering organization at a major global payments technology company, setting technical direction and strategy for fraud detection, computer vision, large language model, and generative AI applications, and has driven significant measurable business impact including multimillion-dollar annual cost savings and material improvements in fraud detection performance. Prior to this role, Expert held senior engineering leadership positions at a major global social media and technology company, leading search and product ranking teams supporting products used by billions of active users, and at a major global financial services firm, where Expert led engineering teams developing data science and visualization tools supporting investment banking operations and large-scale credit risk management.
Earlier in Expert's career, Expert served as Principal Engineer and Technical Advisor to a regional CEO at a major global industrial technology conglomerate, providing technical leadership on machine learning applications for global rail systems, transportation, and logistics, for which Expert received an internal corporate patent award. Expert has extensive experience building and scaling engineering organizations from the ground up, hiring and mentoring both individual contributors and management talent, and has also served as a computer science instructor for an international academic program at a major research university.
Education
| Year | Degree | Subject | Institution |
|---|---|---|---|
| Year: 2014 | Degree: Master of Science | Subject: Computational Science and Engineering | Institution: Harvard University |
| Year: 2014 | Degree: BA & BS | Subject: Computer Science & Business Administration | Institution: University of California, Berkeley |
Work History
| Years | Employer | Title | Department |
|---|---|---|---|
| Years: 2023 to Present | Employer: Undisclosed | Title: Senior Engineering Leadership | Department: Artificial Intelligence, Machine Learning, and Technology |
Responsibilities:• Leads an organization of 25 (3 managers, 21 machine learning engineers, 1 principal technical lead), setting technical direction and strategy for payment intelligence ML models, computer vision models, large language models, and multi-modal generative AI applications; achieved a 21% uplift in smoothed recall and $13 million in yearly savings.• Leads development of highly scalable ML infrastructure (99.9999% availability, ultra-low latency) supporting fraud detection and smart refund models, including company-wide migration toward deep neural network architectures. • Establishes organizational charter, roadmap, and core business KPI metrics for foundational ML development (ML pipeline, CI/CD, auto-train/deploy, embeddings) supporting a key fraud detection product. • Leads model specialization and transfer learning applications for regional fraud detection and mitigation policies, increasing authorization rates by 35% ($7 million in yearly savings). • Hired and retained high-performing talent (15 new hires, 100% retention over the past year) and built 3 sub-organizations from scratch, mentoring managers and individual contributors. |
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| Years | Employer | Title | Department |
| Years: 2022 to 2023 | Employer: Meta (formerly Facebook) | Title: Senior Engineering Leadership, Growth, Search and Ranking | Department: |
Responsibilities:• Led system architectural design and product scoping discussions across 7 cross-functional teams with senior leadership, including prioritization and trade-off discussions with product VP leadership.• Led a Search & Product Ranking team (3 managers, 11 engineers) optimizing recommender systems for a consumer marketplace product scaled to 2 billion+ active users, launching 15+ consumer-facing product features and running 75+ statistically significant A/B tests across 50+ product variants. • Developed a data-driven product strategy using machine learning to identify significant user actions, driving user retention (+57% YoY), call-to-action engagement (+75% YoY), and transaction conversion (+91% YoY). • Built the Search & Product Ranking team from scratch, hiring 8 engineers and participating in promotion calibration committees. |
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| Years | Employer | Title | Department |
| Years: 2017 to 2021 | Employer: J.P. Morgan | Title: Engineering Manager, Machine Learning, Data Science & Analytics | Department: |
Responsibilities:• Led 8 direct reports in launching a large-scale data visualization initiative analyzing 350,000+ rows of raw data, reducing costs by more than 25% and contributing to a 12% increase in deal fees generated over 3 months.• Led data strategy workstreams (Python, Java, SQL) managing over $6.0 billion in credit exposure across 60+ investment banking clients, informing merger, acquisition, and financing decisions, including work on a major corporate sustainability bond issuance. |
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| Years | Employer | Title | Department |
| Years: 2014 to 2017 | Employer: Siemens | Title: Principal Engineer & Technical Advisor, Rail Systems and Mobility & Logistics | Department: |
Responsibilities:• Served as Principal Engineer and Technical Advisor to the regional CEO, providing technical leadership on ML-powered global rail systems, transportation, mobility, and logistics initiatives, unlocking $1.5 million in annual savings.• Received an internal company patent award for related technical work in 2015. |
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Career Accomplishments
| Licenses / Certifications |
|---|
| Certificate in Technology and Entrepreneurship — University of California, Berkeley, Sutardja Center for Entrepreneurship & Technology |
| Awards / Recognition |
|---|
| • Siemens Patent Award (2015), for technical contributions in rail systems/mobility and logistics • Gates Millennium Scholarship • Adobe Research Technology Scholarship • Grace Hopper Scholar |
| Publications and Patents Summary |
|---|
| Received an internal corporate patent award in 2015 in connection with technical work in rail systems and logistics; specific patent number/title not provided in the source materials. |