Analytics, Data Products & AI Lead

Job Description

Private Markets Secondary Investment Data Analytics, Data Products & AI Lead | Neuberger Berman

The Tone:
This is a full-time role at Neuberger Berman, located in the USA. Neuberger Berman is actively building a high-performance Secondary Data Strategy capability. This role is crucial for strengthening data quality, analytical insight, and scalable reporting across the firm’s private markets secondaries platform. The individual will operate at the intersection of investment data, technology, and business process design to improve how data is captured, structured, and activated.

The TL;DR
• Role: Full Time
• Location: In-person, USA
• Pay: $175000–$190000 yearly
• Team: Secondary Data Strategy team
• Mission: Owns the analytics, AI, automation, and client-data-product layer of the Secondary Data Strategy function.
• Tech Stack: CapIQ, PitchBook, Preqin, Bloomberg, VBA, SQL, Python, LLMs, NLP, OCR, intelligent document processing, OpenAI, Claude, Python ML libraries, LLM APIs

What You’ll Actually Do
• Lead the analytics and data product agenda, translating business needs into scalable reporting, insight, and workflow solutions.
• Design and enhance the intelligence layer that supports secondary investment data, including standardized reporting, analytical views, and client deliverables.
• Drive AI- and automation-enabled data extraction initiatives to improve efficiency, consistency, and scalability in data capture.
• Oversee the development and maintenance of client and RFP datasets, ensuring data is decision useful and presentation-ready.
• Partner cross-functionally with investment teams, product specialists, technology, data management, and operations to prioritize and execute strategic initiatives.

The Must-Haves
• Background: Senior level. Strong background in analytics, data product development, or data strategy, with an ability to convert complex business requirements into practical solutions.
• Experience: 6–9+ years of relevant experience in analytics, data products, business intelligence, financial data strategy, or a related function, with hands-on experience applying AI/ML to unstructured document and data extraction.
• Skills: Practical understanding of large language models and generative AI; ability to design and oversee AI-enabled data pipelines and automation workflows; strong communication and stakeholder management skills; high degree of ownership and structured problem-solving ability.
• Bonus: Private markets or secondaries domain knowledge; familiarity with CapIQ, PitchBook, Preqin, and Bloomberg; working knowledge of VBA, SQL, and/or Python; experience with data modeling, reporting architecture, or financial data structures; experience with AI/ML frameworks and tooling (e.g., Python ML libraries, LLM APIs/frameworks such as OpenAI, Claude, or similar).