Operations

• Independently own ad hoc analysis, reporting, and sales strategy for G2's recurring revenue and advertising businesses
• Scope and drive projects, partner cross-functionally to align and execute, and use data-driven thinking to inform go-to-market decisions, forecasting, and annual planning
• Partner with Sales leadership across recurring revenue and advertising businesses and make recommendations shaping go-to-market strategy
• Determine approaches for ad hoc analyses across multiple data sets and tools, including customer segmentation, win/loss trends, pipeline health, and white space
• Identify performance trends and translate findings into actionable recommendations for Sales leadership
• Build and maintain recurring and ad hoc reporting, dashboards, and business review materials
• Provide Sales leadership with real-time visibility into pipeline, bookings, and quota attainment
• Partner with Finance & Strategy, Functional Sales Operations, and Strategy, Planning & Insights to streamline shared reporting processes and deliverables
• Run retrospectives when projects or analyses do not land as expected and turn findings into improvement recommendations

Senior Sales Strategy – Operations Manager

Product Manager

• Own the product strategy and roadmap for G2 UGC
• Define signals and systems improving relevance, recency, completeness, authenticity, and decision value
• Establish coverage and recency standards for different product segments
• Balance coverage, volume, quality, cost, and speed
• Partner with Research, Data, and AI teams on quality measurement, trust signals, moderation, and safe AI use
• Own the contributor journey from invitation through contribution, verification, approval, publication, and reuse
• Build adaptive collection experiences using context, dynamic questions, and AI assistance
• Define requirements for offsite, embedded, event-based, and “review now, verify later” collection
• Design and test incentive and value-exchange models
• Instrument funnels and run experiments on completion, acceptance, cost, defects, and publication time
• Own customer capabilities for discovering, configuring, activating, distributing, and measuring UGC
• Develop reusable surfaces, permissions, integrations, APIs or exports, and performance measurement
• Partner with Revenue, Customer Success, Marketing, and Ecosystem teams on activation patterns
• Connect UGC availability and usage to retention and expansion outcomes
• Connect UGC supply and quality to discovery, comparison, evaluation, and decision-making experiences
• Apply trusted evidence and trust primitives to evaluations, comparisons, and AI-native buying experiences
• Identify and scale new forms of UGC
• Stay close to buyers, contributors, and customers to guide the roadmap

Principal Product Manager – UGC

Data Scientist

• Own strategy and roadmap for exposing and activating G2 data through APIs, MCP, strategic integrations, and developer and partner surfaces
• Own the integration hub service, developer portal, and public-facing surfaces for Marketing Solutions customers, Data Solutions customers, and partners
• Rationalize and migrate the integration portfolio
• Define reusable platform capabilities across customers, partners, and use cases
• Identify partners that expand MCP surface area and customer value
• Decide whether use cases belong in MCP, an API, or a custom integration
• Prioritize investments based on customer evidence, revenue opportunity, partner readiness, technical leverage, and strategic differentiation
• Make build, buy, partner, and defer decisions
• Work with Engineering and Data on APIs, data contracts, authentication, permissions, reliability, and developer experience
• Prototype integrations and ship targeted code to accelerate learning or unblock delivery
• Create reusable patterns for exposing workflows through MCP
• Translate technical constraints and architecture into customer and business tradeoffs
• Own the Data Solutions roadmap for revenue and pipeline growth
• Understand how investors, financial institutions, AI labs, and other customers use G2 data
• Shape offerings, including data coverage, packaging, pricing, delivery options, and customer experience
• Support customer opportunities through discovery, technical evaluation, and pilots
• Improve data quality, coverage, freshness, documentation, and delivery
• Identify adoption barriers, renewal risks, and expansion opportunities
• Productize repeated commercial and partner needs
• Define requirements and launch plans for partner-enabled MCP capabilities and integrations
• Lead legacy integration cleanup and migration with customer communication and deprecation plans
• Create planning and feedback loops across Product, Revenue, Partnerships, Customer Success, and Marketing
• Give commercial teams visibility into capabilities, roadmap intent, dependencies, and tradeoffs
• Balance near-term needs with durable platform strategy
• Define contribution across revenue, MCP adoption, partner-expanded surface area, migration progress, reliability, retention, renewals, and expansion

Principal Product Manager, Data Solutions – Ecosystem

Artificial Intelligence

• Define what to build and why by turning customer insights into product hypotheses, testing them, and creating roadmaps
• Balance user needs, business outcomes, and technical feasibility
• Move fluidly across product management, engineering, and design without handoffs
• Write production code, prototype in low-code/AI environments, and work deeply with engineering partners
• Use AI coding tools to build quickly while maintaining quality
• Design AI-powered experiences involving LLMs, agents, and AI workflows
• Translate AI behavior into useful and trustworthy product experiences
• Distinguish AI features from AI foundations
• Talk to customers and users to drive discovery
• Turn customer conversations into working prototypes quickly
• Operate independently and improve the effectiveness of colleagues
• Communicate with executives, engineers, and go-to-market teams
• Align stakeholders while maintaining momentum

Senior AI Product Builder

Manager

• Lead development and execution of G2's AWS partnership strategy for scalable, repeatable revenue growth
• Cultivate relationships with key stakeholders at G2 and AWS
• Secure executive alignment across partner and internal stakeholders, including C-suite and product leaders
• Identify and pursue co-selling opportunities through the hyperscaler ecosystem
• Activate, enable, and coach internal sales teams on partner co-sell plays
• Build joint GTM plans with AWS industry verticals and regional PDM and sales field teams
• Use AWS partner programs and systems, including Co-Sell, MPOPP, POC funding, MDF, WMP, PRM, ACE Pipeline Manager, and Partner Central, to drive pipeline and revenue outcomes
• Connect AWS, G2 sales teams, and strategic accounts on active deals
• Develop and implement technology integrations between G2 and the hyperscaler platform
• Align with product and engineering teams on integration priorities and partnership roadmap
• Collaborate on joint marketing initiatives to generate demand and awareness
• Manage partner pipeline forecasting and track regional performance
• Track and analyze alliance KPIs and identify continuous improvements
• Build scalable AI-enabled workflows and tools for co-sell motion and enablement
• Monitor launches, product changes, and leadership shifts and share updates with G2 leadership

Senior Cloud Alliances Manager

Engineering Manager

• Scope feasibility and effort for evaluating software-vendor agents
• Own the full stack of the core evaluation system, including admin and API surfaces and evaluation workflow dispatch
• Design reusable evaluation system primitives across software verticals
• Turn integration onboarding and maintenance processes into repeatable AI skills or agents
• Monitor emerging agent-evaluation frameworks and techniques
• Establish industry-accepted methods for distributing evaluation results
• Collaborate with data science peers to develop proprietary benchmarks
• Lead, mentor, and provide technical leadership to a core engineering team
• Promote the use of evaluations in agent-oriented products across the organization
• Deliver useful and credible evaluations of live software-vendor agents
• Apply agent-first engineering techniques to deliver work to production

Software Engineering Director, Agentic Evaluations

• Shape how experimentation is conducted and how data science informs product decisions
• Connect software vendors with the right buyers through G2 products, including ads, reviews, and agentic evaluation
• Partner with stakeholders to modernize existing products and develop new products in an AEO-driven, privacy-constrained landscape
• Build models, design auctions, and ship production systems as a hands-on individual contributor
• Mentor team members and evangelize data science best practices across the company
• Own the experimentation standard for G2 and G2 Digital Markets
• Consolidate practices into a documented approach covering experiment design, randomization, metrics, guardrails, sample size, duration, and interpretation
• Work with engineering teams on instrumentation, assignment, and platform behavior
• Define end-to-end experimentation capability requirements, including platform, telemetry, metric layers, analysis tooling, review process, and organizational practices
• Develop methods for different traffic volumes and decision speeds
• Evaluate and operationalize modern experimentation methods
• Teach data science across product, engineering, and business stakeholders
• Improve the quality of experiment-result interpretation and communication

Principal Data Scientist

Financial Planning and Analysis

• Own the consolidated three-statement model across all US, India, and Spain entities
• Lead monthly consolidation, including intercompany eliminations and entity roll-ups, with Accounting and the Controller's organization
• Track risks and opportunities and bridge consolidated actuals to plan and forecast
• Build and maintain the capital allocation framework
• Lead scenario and sensitivity analysis for growth, margin, and free cash flow trade-offs
• Partner with Corporate Development on M&A deal models, integration economics, and post-acquisition tracking
• Own consolidated MBR, Board deck financials, and investor reporting
• Deliver executive-ready analysis of performance against goals, budgets, and forecasts
• Partner with the CFO and executive business partners on financial insight and decision-making
• Ensure consistency and accuracy of externally and Board-facing financial figures
• Lead the consolidated annual operating plan and long-term plan
• Improve consolidated budgeting and forecasting in the planning tool
• Manage and develop the Corporate Senior Analyst
• Drive automation and AI adoption to scale consolidation and reporting processes