Principal Product Manager, Data

Kiavi • San Francisco, PA

1d • Remote

About The Position

Kiavi is hiring a Principal Product Manager to partner with Data leadership and connect business needs to the work of its cross-functional Data organization, which includes Data Science, Risk Analytics, MLOps, AI/Data Engineering, and Data Analytics. The role drives machine learning, generative AI, and data products from concept to production, with accountability for measurable business outcomes—not just launches.

The product portfolio includes ML and AI models that automate lending decisions across valuation, underwriting, and construction draws; GenAI document understanding; internal data tools for Risk, Operations, and Sales; third-party data partnerships; and data platform priorities. The role requires close coordination with teams that bring data products to customers, as well as partnership with Data, Engineering, Operations, Design, Finance, Legal, and other business groups.

The Principal Product Manager will operationalize the Data XFN roadmap and OKRs, build evidence-based business cases, manage delivery and dependencies, guide model evaluation and governance, and measure financial and operational impact. The position also involves hands-on prototyping with AI and low-code tools, SQL-based analysis, technical collaboration on architecture, vendor and data acquisition, and clear communication of progress and outcomes. The posting says the position can be remote in approved hiring regions, while the qualifications also specify being located in Pittsburgh or San Francisco with the ability to come into the office to collaborate with teammates.

Requirements

• At least 6 years of product management experience, including complex technical or data products built with data scientists and engineers.
• A builder’s mindset, including turning ideas into working prototypes and proofs of concept before engineering commits.
• A record of taking ML or GenAI products from 0 to 1 and into production, with demonstrated business impact in dollars or hours.
• Experience managing cross-team initiatives, establishing sustainable processes, and coordinating releases and priorities.
• Strong business case skills, including sizing, forecasting, ROI, and obtaining sign-off from Finance and executives.
• Ability to lead through influence across a large, decentralized group of teams and stakeholders with strong opinions.
• Hands-on technical fluency with SQL, cloud data warehouses, APIs, event-driven systems, and low-code tools such as Retool or Zapier.
• Daily practical use of AI tools for writing, analysis, prototyping, and code.
• Experience with model evaluation, human-in-the-loop QA, and production monitoring.
• Clear written and verbal communication, from executive narratives to detailed specifications.
• Bachelor’s degree in Computer Science, Engineering, Data Science, Finance, or a related field.
• Located in Pittsburgh or San Francisco and able to come into the office to collaborate with team members.

Nice To Haves

• Lending, mortgage, or real estate experience, especially in valuations, underwriting, title, or draws.
• Experience buying and integrating third-party data such as property, MLS, lien, or zoning data.
• Experience with outcome-based OKRs at individual, team, department, and company levels.
• Experience integrating products, data platforms, or teams after an acquisition.
• An advanced degree.

Responsibilities

• Partner with Data leadership to operationalize the Data XFN roadmap and track quarterly OKRs, ensuring initiatives connect to goals and have owners across contributing teams.
• Facilitate data leadership decision forums, prepare relevant data for decisions, and surface difficult trade-offs.
• Identify new data and AI opportunities and develop proposals that include potential size, ROI, risk, and a go/no-go recommendation.
• Develop program milestones, track progress and cross-team dependencies, mitigate risks, and manage communications.
• Manage priorities across multiple data science and development teams and concurrent projects.
• Write business cases with conservative and aggressive forecasts, obtain Finance sign-off before work begins, and measure outcomes such as cost, quality, and hours saved.
• Work with FP&A and Operations to translate efficiency gains into approved capacity and budget changes, and identify savings in vendor spend and manual work.
• Drive ML and GenAI products from discovery or prototype through proof of concept, shadow mode, pilot, and production.
• Work with application engineering teams and product counterparts to run pilots, learn quickly, and move products toward production.
• Establish phased QA, human evaluation, and feedback loops to build operational trust in models before scaling.
• Guide launches through model governance, legal and compliance review, and user training.
• Analyze underperforming models with Data Science and recommend improvements, a pivot, or stopping the work.
• Coordinate execution across teams by managing dependencies, tracking milestones, removing blockers, and ensuring initiatives reach production.
• Align Engineering, Operations, Design, and Data on shared definitions, prototypes, and written specifications before development.
• Build alignment with leaders ahead of group decisions and secure unplanned engineering capacity by demonstrating the opportunity’s value.
• Partner with Operations, Underwriting, Sales, Servicing, Legal, and Finance teams, resolving obstacles and communication gaps.
• Identify, assess, and make the case for new datasets; manage procurement, vendor relationships, and renewals.
• Build prototypes with low-code and AI tools, write SQL, use AI to answer questions, and use AI coding tools to ship small changes.
• Understand APIs, queues, and data pipelines well enough to support engineering architecture decisions and encourage AI-first ways of working.
• Communicate the Data team’s work through newsletters, launch notes, and product reviews; provide regular updates on timelines, outcomes, projections, and OKR risks.
• Mentor Product Managers on business cases, experimentation, and GenAI.

Benefits

• Free employee-only medical, dental, and vision insurance; dependents receive a heavily discounted premium.
• Annual employer HSA contribution for employees enrolled in an HDHP: $1,000 for individual coverage or $2,000 for dependent coverage.
• Short- and long-term disability insurance, group life insurance, and AD&D coverage at 1x annual salary.
• For remote workers, a one-time office setup reimbursement of up to $500 and a monthly $85 internet and phone stipend.
• For in-office workers, employer contributions to a commuter benefits account for parking or public transportation.
• Flexible time off with no strict limits, subject to manager approval.
• Up to 8 weeks of paid leave for medical or caregiver purposes and 12 weeks of paid maternity/paternity leave; short-term disability leave is also available for birthing mothers.
• 401(k) plan managed by Fidelity, with a 100% company match on contributions up to 3% of compensation or $8,000, whichever is less; employer contributions are immediately vested.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal