Director Product Management
Posted on 4/2/2024

1,001-5,000 employees

Digital platform for simplified loan management and servicing
Company Overview
Sagent stands out as a leading company in the financial technology sector, providing robust platforms that streamline loan origination and servicing, enhancing customer experience and fostering long-term relationships. Their technology not only empowers consumers to manage their homeownership journey from anywhere but also offers servicers cost efficiency, scalability, and compliance across market cycles. Sagent's competitive edge lies in its commitment to making loans and homeownership simpler and safer for millions, setting a high industry standard.

Company Stage


Total Funding





King of Prussia, Pennsylvania

Growth & Insights

6 month growth


1 year growth


2 year growth

Dallas, TX, USA
Experience Level
Desired Skills
Market Research
Product Management
Product Research
Product Strategy
  • Bachelor's Degree in business, computer science, and/or related field
  • 10+ years of experience in Mortgage servicing, including any area, such as Support
  • Previous experience managing software product or educational equivalent (e.g., Pragmatic Institute, 280 Group, others)
  • 3+ years of experience working on an Agile team in SaaS product management
  • Excellent oral, written, and presentation skills with the ability to convey technical concepts to non-technical stakeholders clearly
  • Strong leadership skills with experience leading cross-functional teams and driving products to completion
  • Analytical mindset, comfortable using data to inform decision-making and product improvements
  • Willingness to travel occasionally (up to 20%)
  • Develop and execute product strategies that align with the company’s vision and objectives
  • Identify market opportunities, conduct market research, and stay up to date with industry trends to ensure our product meets customer needs
  • Gather business needs and translate them into detailed business requirements, guiding engineering and development teams in defining functional and technical requirements
  • Play an integral role in designing and documenting business processes for new or updated technology
  • Build strong and effective relationships with cross-functional business leaders to establish product strategy
  • Lead cross-functional teams throughout the product development process, collaborating with design, engineering, marketing, and other stakeholders to deliver a high-quality product on time and within budget
  • Coordinate the product roadmap with the broader product team
  • Participate in day-to-day team activities and handle assigned duties
  • Communicate complex concepts clearly and effectively to both technical and non-technical audiences
  • Keep stakeholders informed about project progress, potential risks, and any changes in product direction
  • Identify and address customer challenges, delivering impactful solutions that enhance their experiences
  • Evaluate and manage feature requests to prioritize product development efforts
  • Monitor product performance and gather feedback from customers, sales teams, and other sources
  • Analyze customer experiences to identify friction points and contribute to creating seamless and effortless interactions
  • Demonstrate an expert understanding of the product domain and the ability to identify and solve complex challenges
  • Use data driven insights to make informed decisions and continually improve product performance
  • Partner with data scientists and machine learning engineers to develop and deploy AI models for various mortgage servicing tasks, such as risk assessment, fraud detection, and customer support
  • Oversee the training, testing, and optimization of AI models, ensuring accuracy, fairness, and compliance with regulatory requirements
  • Ensure that AI-powered solutions comply with relevant regulatory requirements, industry standards, and best practices, particularly in areas such as data privacy, security, and fair lending
  • Proactively identify and mitigate risks associated with AI implementation, such as bias, model drift, and ethical considerations