Pearl

Product Manager

• Drive coordination and execution across multiple concurrent product initiatives.
• Partner with Engineering leadership to ensure initiatives move efficiently from discovery through delivery.
• Act as initiative lead or embedded senior PM on high-priority projects as needed.
• Help translate product strategy into actionable plans, requirements, and delivery milestones.
• Identify risks, dependencies, and resource gaps early and help teams resolve them.
• Strengthen product operating rhythms including roadmap planning, initiative tracking, and delivery accountability.
• Help maintain clarity across teams during periods of rapid change or evolving direction.
• Support prioritization decisions by balancing strategic goals, customer needs, and delivery realities.
• Contribute to product strategy and roadmap development in partnership with the SVP Product.
• Lead or support customer research, problem discovery, and validation of new opportunities.
• Help shape Pearl SCORE experiences and related platform capabilities across consumer and partner workflows.
• Serve as a primary coordination partner between Product and Engineering teams.
• Collaborate closely with Data Science and Standards teams to translate complex modeling and scoring concepts into clear user experiences.
• Partner with BD and Marketing teams to ensure product initiatives support commercial and partner outcomes.
• Help align stakeholders around priorities, timelines, and product direction.
• Provide coaching and mentorship to product managers and designers.
• Help strengthen product craft, documentation quality, and discovery practices.
• Foster a culture of ownership, clarity, and collaborative problem solving.
• Identify and lead opportunities to integrate AI and machine learning into Pearl’s consumer and partner experiences.
• Leverage modern AI tools to accelerate product discovery, documentation, analysis, and delivery workflows.
• Ensure Pearl remains competitive and forward-looking in how intelligence is embedded into the platform.

Principal Product Manager

Full-stack Engineer

• Build and ship features across Pearl’s clinical product suite using AI-assisted development workflows
• Use tools like Cursor, Claude Code, and Gemini to accelerate code generation, debugging, documentation, and code review
• Architect scalable systems that integrate with Pearl’s ML and computer vision pipelines
• Drive improvements in engineering velocity and quality by identifying where AI tooling can reduce friction
• Mentor teammates on effective AI-augmented development practices

Senior Software Engineer

Operations

• Proactively identify revenue leaks and conversion opportunities across the funnel, from lead quality and demo show rates to SDR-to-AE handoff loss, and own the operational fixes that move the number
• Treat the funnel as a growth asset: continuously test, instrument, and optimize each stage to compound conversion rate improvements across SMB and DSO motions
• Surface and prioritize the highest-leverage interventions, sequencing, enrichment, routing, timing, and drive execution with Sales and Marketing rather than waiting for leadership to diagnose the problem
• Build the measurement infrastructure that makes growth opportunities visible before they become misses: forecast gaps, segment underperformance, channel attribution anomalies
• Partner with Sales leadership to find hidden capacity in the existing pipeline: stalled deals, under-worked segments, and low-touch accounts with expansion potential
• Own end-to-end visibility into the revenue funnel, from lead creation through closed-won, ensuring every stage is instrumented, defined, and trusted across SMB and DSO motions
• Partner with the Data team to drive accuracy in pipeline, activity, and sales forecasting data across SMB and DSO segments
• Design and maintain lead routing, territory assignment, opportunity stage definitions, and pipeline hygiene standards
• Build and manage the outbound tooling ecosystem (Clay for enrichment, Nooks for parallel dialing, and future tools) with a focus on rep productivity and data quality
• Own SDR and AE workflow automation: sequences, task queues, lead scoring models, and handoff triggers between SDR → AE → CS
• Partner with Sales leadership and the Outbound Sales Leader to build forecasting models, pipeline coverage reporting, and rep productivity dashboards
• Drive sales process standardization and compliance — ensuring reps follow defined stages, capture required fields, and maintain data discipline
• Own the marketing technology stack and its integration with CRM: forms, landing pages, email automation, nurture workflows, lead scoring, and lifecycle stage management
• Partner with Demand Generation to build and maintain marketing attribution models (first-touch, multi-touch, influenced pipeline) that connect marketing activity to pipeline and revenue
• Manage website operational workflows: form routing, chatbot logic, content personalization triggers, and conversion tracking (excluding paid media execution)
• Own list management, segmentation, data hygiene, and compliance (CAN-SPAM, opt-out management) across all marketing channels
• Partner with Demand Generation and Content teams to operationalize campaigns — building the backend workflows that turn strategy into execution
• Partner with Customer Success to build the post-sale operational infrastructure: onboarding workflows, activation tracking, health scoring, renewal/expansion triggers, and churn risk alerting
• Own the CS tech stack integration layer — ensuring customer lifecycle data flows cleanly between HubSpot, product analytics, and support systems
• Design NRR and gross retention reporting frameworks that CS leadership and the exec team rely on for strategic decisions
• Operationalize the customer journey: define handoff points from Sales → Onboarding → CSM → Renewal, with SLAs and escalation paths at each stage
• Partner with the Product team to build self-sign-up and cross-sell infrastructure that reduces friction in the acquisition motion and enables product-led revenue
• Connect the product stack (e.g., Pendo) to the broader marketing and customer success stack to create a unified view of customer behavior across the lifecycle
• Design product-led reporting frameworks that product leadership and the exec team rely on for strategic decisions
• Lead Pearl's adoption of AI and LLM tools across the commercial stack — from AI-assisted prospecting and outreach personalization to automated pipeline analysis and CS workflow intelligence
• Continuously evaluate emerging tools (AI agents, LLM-powered enrichment, conversational AI, autonomous workflow tools) and make build-vs-buy decisions that compound operational leverage
• Build automated systems that reduce manual ops work across Sales, Marketing, and CS — using AI to scale output without scaling headcount linearly
• Serve as the internal expert and evangelist on what AI can unlock in a go-to-market context, bringing POVs to leadership proactively rather than waiting to be asked
• Serve as the operational connective tissue between Sales, Marketing, CS, Product, and Finance — ensuring systems and processes are aligned and information flows without friction
• Own vendor evaluation, selection, and management for growth tools and platforms
• Drive operational planning cadences: QBRs, monthly operating reviews, territory planning, and capacity modeling in partnership with growth leadership

Director of Growth Operations

Data Scientist

• Lead the design and execution of data science projects that directly impact Pearl’s AI products and business outcomes
• Analyze large, complex datasets to uncover insights, trends, and opportunities
• Build and validate statistical models, experiments, and predictive analyses
• Partner with engineering and ML teams to productionize data science work
• Define metrics and KPIs to measure product performance and clinical impact
• Communicate findings clearly to technical and non-technical stakeholders
• Mentor junior data scientists and promote best practices across the team

Senior Data Scientist

Technical Recruiter

• Attracting, assessing and hiring talent for Technical positions in our Engineering & Product organization as well as occasional G&A functions
• Developing high quality, multi-channel talent processes that ensure we find and hire top talent
• Effectively managing key stakeholders to align on key competencies for important hires - departmental leaders and hiring managers.
• Influence and educate new hiring managers on process, interview best practices, and decision making
• Implement and scale structured hiring processes that will reduce bias and uplevel Pearl’s hiring decision making
• Leverage data to analyze sourcing stats and pipeline pass-through rates to optimize the hiring process