Product Manager, Agentic Data Operations

Chronograph • New York, NY

8d • $150,000 - $200,000 • Hybrid

About The Position

Chronograph is seeking an analytically rigorous, operationally minded Product Manager to transform how private capital data is processed. This senior role will advance the Data Operations platform from a technology-supplemented process toward automated, agent-driven pipelines using LLM-native extraction. The Product Manager will own the roadmap for Data Operations processes and work with senior leadership, Engineering, applied data extraction teams, Design, and Data Operations leadership to scale systems that convert GP and fund reporting documents into structured data for investors. The role includes optimizing operational workflows, setting confidence thresholds for automated extraction and reconciliation, improving document aggregation and routing, and identifying opportunities to expand the scope of data processed. The position also manages and develops a direct report.

Chronograph provides cloud-based analytics and data management solutions for private capital markets. Its Data Operations team collates, extracts, normalizes, and reconciles data across private capital sub-asset classes for Limited Partner clients. The role is based around transforming data delivery while maintaining the accuracy standards required in financial services.

Requirements

• At least 6 years of experience in product management, technology consulting, or fund administration operations.
• Experience owning at least one operational or platform transformation end to end.
• Deep experience in process evaluation, instrumentation, and optimization, with hands-on knowledge of applying technology to improve productivity and quality.
• Demonstrated upskilling in AI and agentically enabled processes, with continuous learning as a core motivation.
• Semi-technical product judgment, including reasoning about accuracy and confidence thresholds, deciding when automation is safe versus when human review is needed, and expressing that logic clearly for engineers.
• Ability to own a transformation agenda and direct a domain expert who provides depth on internal processes.
• Comfort with private capital markets or ability to quickly learn how GPs and LPs exchange fund data.
• Strong analytical, project leadership, and communication skills.
• Positive attitude, sense of humor, and creativity.

Responsibilities

• Transform the Data Operations function toward an agent-driven pipeline that automates repetitive tasks and increases capacity, timeliness, and efficiency.
• Develop and maintain a detailed product roadmap, prioritizing initiatives according to business needs, technical feasibility, and resource availability.
• Evaluate and continually improve operational processes, particularly touchpoints requiring human intervention.
• Design classification and reconciliation logic that routes documents to automated processing or human review according to accuracy and confidence thresholds.
• Instrument and track throughput and accuracy, connect operational efficiencies to financial objectives, and use metrics to guide the roadmap.
• Partner with Engineering to specify requirements, with Design to shape review workflows, and with Data Operations leadership to identify opportunities and lead change management.
• Manage, develop, and motivate a direct report, fostering a collaborative, high-performance work environment.
• Redesign document aggregation and organization for the extraction pipeline, reduce manual steps, and identify opportunities to expand processed data into new commercial opportunities, end markets, and asset classes.

Benefits

• Flexible work arrangements, including in-person and hybrid options
• Competitive salary
• Equity participation
• 401(k)
• Unlimited and flexible vacation
• Generous health benefits
• Team week events at the Brooklyn, NY headquarters three times annually for all employees
• Fully paid parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed