Analytics Manager

At Forge, we know our team is our greatest asset. As technology innovators in the private market, our vision is to deliver a richer future for everyone. We live that vision through our values of being bold, accountable, and humble. We experience the value that our vision brings to the world every day, helping the teams behind the greatest innovations of our generation—from space travel to artificial intelligence and more. With liquidity solutions, exclusive data and insights, a custody offering, and a vibrant marketplace, Forge's goal is to build the best-in-class technology infrastructure to power a global private market that is transparent, accessible, and seamless for companies, their employees, and investors.

About the role

Forge Global is seeking an Analytics Manager to help shape the future of private market investing through data, analytics, data science, and AI. This is a highly visible individual contributor role with no direct reports. You will partner directly with leaders across Product, Growth, Revenue, Operations, and Finance to solve complex business problems, identify growth opportunities, and drive measurable outcomes. The ideal candidate is equally comfortable moving between business strategy and technical execution: writing SQL, building predictive models, designing experiments, creating trusted reporting, and turning complex analysis into clear recommendations that drive decisions. You will join a small, high-impact analytics team where ownership is broad, the work is hands-on, and your insights can influence company strategy.

This role requires 2-3 days a week in office in San Francisco, CA.

Responsibilities

• Analytics, Strategy & Business Impact
  • Own analytics strategy and decision support across business domains.
  • Translate ambiguous business questions into analytical frameworks, recommendations, and action plans.
  • Conduct deep-dive analyses to understand customer behavior, marketplace dynamics, product performance, growth opportunities, and business performance.
  • Partner with business leaders to identify opportunities, define success metrics, measure impact, and guide tradeoffs.
  • Design and evaluate experiments that inform product, marketing, and operational decisions.
• Machine Learning & AI
  • Develop predictive and statistical models that improve business outcomes.
  • Identify opportunities to apply machine learning and AI to improve customer experiences, internal workflows, prioritization, and decision support.
  • Partner with Product, Engineering, and business teams to evaluate, prototype, and operationalize practical AI-driven solutions.
  • Apply modern analytical techniques, including machine learning, statistical modeling, automation, and generative AI, where they can create measurable business impact.
  • Help shape how Forge uses analytics and AI responsibly by focusing on practical use cases, measurable value, and trusted outputs.
• Reporting, Data Quality & Enablement
  • Build and maintain dashboards, recurring reporting, and self-service assets that help stakeholders make faster and better decisions.
  • Define and maintain trusted business metrics, KPI frameworks, and measurement standards.
  • Validate data quality, investigate anomalies, reconcile discrepancies, and proactively surface risks in analytical outputs.
  • Partner with data and engineering teams to improve the reliability, usability, and scalability of data used across the business.
  • Automate repetitive analytical workflows and improve team processes, templates, QA checks, and stakeholder workflows.
• Stakeholder Partnership & Leadership
  • Act as a trusted analytics partner and primary point of contact for assigned stakeholder groups.
  • Lead intake and prioritization for analytical work by clarifying goals, scoping projects, setting expectations, and communicating progress.
  • Tell clear, compelling stories with data and influence decisions through evidence-based recommendations.
  • Mentor analysts and stakeholders informally through code reviews, analytical approaches, measurement design, and best practices.
  • Operate independently in ambiguous, fast-moving environments while knowing when to escalate risks, tradeoffs, or decisions.

Requirements

• 5-7 years of experience in analytics, data science, quantitative strategy, or a related field.
• Bachelor’s degree.
• Advanced SQL skills and the ability to independently move from raw data to actionable recommendations.
• Strong Python experience for statistical analysis, machine learning, and automation.
• Experience designing and analyzing experiments, including A/B testing, causal measurement, or related methods.
• Experience building predictive models or applying machine learning techniques to real-world business problems.
• Experience with platforms such as Snowflake and Looker.
• Strong communication skills with the ability to translate complex analytical concepts into clear business recommendations.
• Proven ability to influence decisions through data and build strong cross-functional partnerships.
• Comfort operating in ambiguity with significant ownership, autonomy, and accountability for outcomes.
• Physical requirements: operate a computer for 8 hours per day; give and receive detailed information through verbal and written communication.

Preferred Qualifications

• Experience deploying, operationalizing, or monitoring machine learning models in a business environment.
• Experience with customer lifecycle, marketplace, fintech, investment, product, or growth analytics.
• Experience using generative AI or LLM-based tools to accelerate analytical workflows or build practical business solutions.
• Familiarity with product analytics, marketing measurement, experimentation platforms, or event instrumentation.

Pay

For residents of San Francisco, CA the annual salary range for this role is $120,000 - $150,000 + annual bonus. Final offers may vary from the amount listed based on geography, candidate experience and expertise, bonus, and other factors.