Lead Product Manager

Doma is seeking a Lead Product Manager as we build the technology that makes real estate closings faster, smarter, and more certain. This individual will be tasked with growing Doma’s revenue and operating leverage by building customer experience and automation solutions to reduce the friction of several steps in the closing process. As a Lead Product Manager, you will help drive strategy across several growth focused metrics, feature development and prioritization of the product roadmap, and alignment across engineering, data science, operations, sales, and marketing and other partners.   

You will focus on a durable capability area (intelligent title search) as well as discrete business outcomes related to that area (continued development of the refinance model linked to company OKRs). In this role you will play a key role in problem-solving across functions, and in shaping the vision, values, and culture of Doma’s Product Team.

What You’ll Do: 

Product Execution & Delivery 

• Own day to day product execution and the roadmap for our only-of-its kind refinance title decisioning platform 
• Start with the outcome: define the customer, the value, and the measurable result for each initiative before designing the solution 
• Translate product strategy into clear requirements, user stories, and acceptance criteria 
• Manage and prioritize roadmap deliverables and milestones across multiple workstreams and teams, making clear trade-offs against company OKRs and capacity 
• Partner closely with engineering, data science, and platform through the entire life cycle to deliver scalable, high-quality solutions 
• Use domain expertise, reporting and analytics, and customer feedback to improve how our automation and AI capabilities perform 

Metrics, Monitoring & Product Health 

• Define and track key product and operational metrics, and own the results against company OKRs 
• Own the health of your capability area, including accuracy, cost, service levels, and reuse across products 
• Monitor trends and proactively identify risks, anomalies, or performance issues 
• Partner with engineering and operations to investigate issues and drive resolution 
• Create dashboards and reporting that improve transparency and accountability 

Partner & Stakeholder Management 

• Act as the product point of contact for internal teams and external partners 
• Bring a point of view to roadmap reviews and leadership: come with a recommendation, communicate what matters, and use debate to sharpen the thinking 
• Partner with business development teams in support of new customer onboarding and implementation, as well as monitor the ongoing detection of pain points and opportunities that can be addressed by our products 
• Make sure dependencies are well understood and documented 

Workflow & Continuous Improvement 

• Collaborate across functions to identify pain points and opportunities for automation, efficiency, and error reduction 
• Establish feedback loops to continuously improve our products, systems, and processes   

Desired Skills & Experience: 

• Experience: 6+ years of relevant product management experience, including leading cross-functional initiatives for B2B, platform, data, or AI/ML-enabled products 
• Impact: A prior focus on delivering impactful enterprise workflow, automation, and/or machine-learning or AI products that positively benefit key customer and business goals. 
• Strategy: Business acumen and a strong data-driven and judgment-driven decision-making skillset. The ability to convert this into a high-ROI roadmap and to make and explain trade-offs between competing priorities. 
• Creativity and Design Thinking: Fearlessly innovative in undeveloped space, with independent identification of differentiated, powerful, and user delightful solutions.  
• Execution: Strong executional abilities to help engineering, data science and others have the necessary context, understanding of goals, and clarity of acceptance criteria. Being able to identify risks proactively and problem-solve to mitigate them. 
• Technical Fluency: Comfort with APIs, data pipelines, and the machine-learning lifecycle (training data, evaluation, monitoring, and retraining), and the ability to evaluate data quality, accuracy, and cost with engineering and data science partners. 
• Communication: Outstanding written and verbal communication skills with an emphasis on communicating technical requirements and solutions to internal and external audiences, including bringing clear recommendations to senior leaders. 
• Collaboration: Ability to drive successful alignment across different internal and external stakeholders and leadership. 
• Autonomy: The ability to work autonomously and constantly being able to convert ambiguity into clarity. 
• Domain (Extra Credit): Experience in title, escrow, mortgage, real estate, or another regulated financial-services workflow, or a demonstrated ability to learn a complex, regulated domain quickly.