Metropolitan Commercial Bank · 1 day ago
AI Scientist
New York, NY
Full-time
Hybrid
Senior Level
$130K/yr - $200K/yrMetropolitan Commercial Bank is a full-service commercial bank based in New York City, recognized for its excellence in banking services. The bank is seeking a VP-level Applied AI & Machine Learning Scientist to design, build, and validate production-grade AI/ML solutions, focusing on high-impact use cases such as fraud detection and AI-assisted decision support.
BankingBusiness DevelopmentCommercial
Responsibilities
Design and implement models for fraud detection, AML alert scoring/triage, AI-generated credit memo drafting and underwriting decision support, contact center AI assistants, and personalization for commercial/treasury use cases
Leverage modern methods: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings and vector databases, transformers, boosting, anomaly/outlier detection, and classical ML
Embed explainability (e.g., SHAP, interpretable scorecards/monotonic models) and conduct pre-/post-deployment bias testing with documented remediation
Produce audit-ready documentation (methodology, assumptions, data lineage, limitations, testing) and register models in the inventory with owners/materiality
Facilitate independent validation/effective challenge; obtain required approvals before deployment; maintain change management and periodic review cadence
Define monitoring, drift thresholds, retraining triggers, and safe rollback/kill-switch procedures; maintain human-in-the-loop checkpoints for high-impact decisions
Package, deploy, and operate models via CI/CD, containerization, and model registry; instrument KPIs/KRIs and alerting dashboards
Operate models natively on Snowflake using Snowpark Python, UDFs/UDTFs, Tasks/Streams, and secure external access where required
Partner with Engineering to integrate models via secure APIs/batch; ensure scalability, resiliency, and observability in cloud/on‑prem (e.g., Snowflake, Azure ML, Databricks)
Design for ECOA/Reg B (adverse action specificity), UDAAP, FCRA, GLBA privacy, and NYDFS 23 NYCRR 500 cybersecurity requirements
Apply privacy-by-design (data minimization, purpose limitation, retention), strong access controls/segregation, and secure SDLC/red teaming for GenAI stacks
Support due diligence, testing, and ongoing monitoring of vendor AI/data providers per SR 23‑4; evaluate conceptual soundness, fairness, and security
Negotiate/verify contractual controls (no vendor training on MCB/NPI, subprocessors disclosure, audit rights, exit/portability)
Ensure AEDT compliance (NYC Local Law 144) for any HR-related AI tools
Collaborate with Model Risk, Compliance/Legal, Cyber/IT, Data Privacy, Internal Audit, and business owners to meet objectives while staying within risk appetite
Communicate complex results, risks, and limitations clearly to technical and non‑technical stakeholders (management committees, examiners)
Evaluate emerging ML/GenAI methods, LLM evaluation techniques, Snowflake‑native capabilities (e.g., vector search, orchestration), and governance tooling; lead POCs within established control gates
Mentor junior staff; promote responsible AI practices, documentation standards, and reproducibility
Qualification
Required
Master's or PhD in a relevant field (Computer Science, Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML, NLP, or model interpretability
Expertise in Python (pandas, scikit‑learn), deep learning (PyTorch/TensorFlow), NLP/LLMs, LangChain, embeddings/vector search, and classic ML
MLOps proficiency with CI/CD, containerization (Docker), registries, and observability; cloud ML (Snowflakes-native ML, Azure ML or Databricks preferred)
Snowflake‑native ML proficiency: Snowpark Python, UDFs/UDTFs, Tasks/Streams; ability to build and operate ML workflows inside Snowflake
Data engineering competency (SQL, ETL/pipelines, Spark/PySpark); ability to work with structured/unstructured data
Explainability (e.g., SHAP) and fairness testing; ability to produce interpretable reason codes for ECOA/Reg B adverse actions as applicable
Strong grasp of SR 11‑7 lifecycle, model documentation, and operational monitoring within three lines of defense governance
Excellent communication; ability to translate technical detail to business/risk stakeholders and drive decisions
Curiosity and problem‑solving mindset; ability to balance innovation with disciplined risk management
Preferred
Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics)
Hands-on with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions; experience with feature management/registry tooling a plus. model registry and pipeline orchestration; Kubernetes a plus
RAG architectures, vector databases, prompt engineering, and LLM evaluation (accuracy, hallucination, safety)
Fairness toolkits and XAI frameworks; experience preparing models for validation, audit, or regulatory exam discussions
Familiarity with SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber)
Ability to work in a constantly evolving environment
Must have excellent written and verbal communication skills
Must be a good listener and good teacher
Demonstrate analytical, troubleshooting and problem-solving skills
The ability to learn new technologies quickly
Self-directed individual with technology and communication skills
Ability to take in multiple sources of information with an understanding of the bigger picture need, want, and operation of the Bank
Collaborative team-player who can find creative and practical solutions in a dynamic work environment
Ability to handle ambiguity, juggle multiple matters at once, and quickly and seamlessly shift from one situation or task to another
Company
Metropolitan Commercial Bank
Metropolitan Commercial Bank provides business, commercial, and personal banking products and services.
Founded in 1999
201-500 employees
H1B Sponsorship
Metropolitan Commercial Bank has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
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Trends of Total Sponsorships
2025 (1)
2024 (2)
2023 (1)
Funding
Current Stage
Growth StageLeadership Team
Nick Rosenberg
Executive Vice President, Chief Technology Officer
Dixiana B.
Executive Vice President and Chief Operating Officer
Recent News
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