Opening and welcome
Andrew Delaney, President & Chief Content Officer, A-Team Group

LEADERS PANEL: The State of Alt Data in 2026 – what’s changed that actually matters

• What’s durable vs what’s hype (AI, private markets, regulation, budgets)
• Where teams are genuinely reallocating spend and effort
• The new “must-have” capabilities for a modern data program

Moderator: Christos Koutsoyannis, Chief Investment Officer, Atlas Ridge Capital
Norman Niemer, Chief Data Scientist, UBS Asset Management
Eliza Raphael, Head of Data Strategy, Jump Trading
David X Martin, Chairman and CEO, Arctium Capital Management

Data Provider Keynote: How to use AI to build better data products

• Entity resolution, normalization, and enrichment at scale
• Productization- transforming raw sources into investable signals
• Quality controls- monitoring drift, breakages, and methodology changes

Fresh features from new to market and leading data vendors

Data Quality Lab

• How different teams define “quality” (and why the definitions clash)
• Practical approaches to improving quality: QC checks, anomaly detection, drift
• Short, tactical takeaways: the checks teams run before trusting a dataset

Mike Soss, Chief Investment Officer, Millburn
Enrico Dallavecchia, President and COO, Arctium Capital Management
Samantha Mait, Data Science Operations Lead, Balyasny Asset Management L.P.

Panel: How funds decide to license a dataset: trials, pitfalls, and what breaks deals

• What really happens during trials (on both buyer and vendor sides)
• Common failure modes: unclear value, integration friction, weak documentation
• The latest compliance concerns to be aware of

Moderator: Eric Duncan, Head of Business Development, Databento
Carrie Anton, Director, Data and Research Management, Jain Global
Don D’Amico, Founder & CEO, Glacier Network
Mark Fleming Williams, Head of Data Sourcing, CFM

Panel: Synthetic Data: When it helps, when it’s a trap, and how to validate it

• Legitimate use cases vs red flags
• Methodologies – how synthetic data is generated and what that implies for risk. Dealing with AI scraping
• Buy vs. build: should this come from vendors or be generated in-house?
• New opportunities

Jeffrey Maron, Managing Director, 7RIDGE
Sarkis Agaian, Senior Quantitative Developer, Laurion Capital Management
Iro Tasitsiomi, Head of Investments Data Science, T. Rowe Price
Yifang Cao, Senior Quant Researcher, Jupiter Research Capital

Closing Discussion: Democratization of alternative data – when everyone has LLMs, what still creates edge?

• Does easier access compress alpha, or shift it to engineering and process advantages?
• “Off-the-shelf” vs proprietary – where differentiation still survives
• Is alpha created via the analysis or the underlying data set? Can the same data set yield very different alpha based on the analysis, and resulting trading implementation?
• What this means for strategy, resourcing, and vendor selection

Moderator: Kathryn Zhao, Adjunct Professor, Cornell University
Gordon Ritter, Chief Investment Officer, Ritter Alpha
Tony Berkman, Former Managing Director, Two Sigma
Evan Reich, Former Head of Data, Verition Fund Management
Duncan Robinson, Director of AI & Optimization – Principal Research Scientist, Franklin Templeton

Drinks reception and networking with sponsors