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Head of Data Science and AI - EAST COAST

44 minutes ago
United States
Full-time
Executive
AI (Artificial Intelligence)
Data Science and Analytics
Azure Generative AI Machine Learning Microservices MLOps Snowflake
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StarCompliance

StarCompliance

StarCompliance is a leading provider of compliance and regulatory software for the financial services industry. They offer solutions that help businesses monitor conflicts, meet regulatory obligations, reduce risk, and comply with confidence. Their pro...

Capital Markets
251-1K
Founded 1999
View All Jobs 4

Description

  • Own the technical strategy and execution roadmap for AI-enabled capabilities across the StarCompliance platform.
  • Drive adoption of generative AI, LLM architectures, predictive analytics, graph intelligence, recommendation systems, and semantic search based on customer value.
  • Define the data foundation strategy and ensure data is clean, trusted, and well governed.
  • Build MLOps capabilities covering model training pipelines, versioning, monitoring, A/B experimentation, and drift detection.
  • Champion practical AI adoption across engineering and product development.
  • Build, mentor, and scale teams across data engineering, data science, ML engineering, and analytics.
  • Align AI and data initiatives with company strategy and commercial priorities in partnership with the CTO and executive team.
  • Co-own the AI roadmap, prioritization, and delivery outcomes with the Product Director, AI & Data Products.

Requirements

  • Proven experience delivering production-grade AI and machine learning systems at scale.
  • Deep experience with generative AI and LLM application architectures, including fine-tuning, prompt engineering, RAG, and agentic frameworks.
  • Strong knowledge of vector databases and semantic search tools such as Pinecone, Weaviate, pgvector, or Azure AI Search.
  • Deep background in modern data engineering, ELT/ETL patterns, and large-scale data pipelines.
  • Hands-on experience with Snowflake or an equivalent cloud data warehouse and data modeling patterns.
  • Strong Azure experience with Azure Data Factory, Azure Synapse, Azure OpenAI Service, and Azure Machine Learning.
  • Strong software engineering fundamentals and experience with cloud-native, microservices, and event-driven architectures.
  • Experience making build-versus-buy-versus-integrate decisions across AI and data tooling.
  • Proven experience building and leading high-performing Data and AI engineering teams.
  • Experience in financial services, regtech, compliance, surveillance, or another regulated industry; strong commercial judgment and commitment to ethical conduct.

Interested in this position?

Apply directly on the company website

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