Senior Product Manager, Upstart

• 5-10 years experience in a product management role focused on technical products or platforms
• Experience building products that serve technical users (e.g. software developers, machine learning researchers, data scientists) -- and a deep understanding of their needs and pain points
• Knowledge of machine learning workflows (e.g. model training, online inference, feature management, etc.)
• Ability to build relationships and effectively collaborate with all levels of the organization, from C-level to individual contributors
• Ability to manage and influence through persuasion, negotiation, and consensus building

Desirable

• Upstart’s Machine Learning Platform team is building a scalable, reliable, and user-friendly ML Platform that enables our machine learning experts to quickly develop and deploy ML models in production
• By building an exceptional platform for machine learning innovation, this team plays a crucial role in advancing Upstart’s core competitive advantage and accelerating our path to becoming the premier destination for consumer credit
• As the Senior Product Manager, Machine Learning Platform at Upstart, you will own the strategy and execution for the tools and services that enable data preparation, feature engineering, and model training workflows for our machine learning teams
• You’ll collaborate with multiple engineering teams across machine learning platform engineering, software engineering, and data engineering to ensure the right data is made available to ML teams for offline research and accurately surfaced to models for online inference
• You’ll drive improvements to the overall speed, cost, and efficiency of our training workflows, ultimately accelerating the speed by which ML teams can research, innovate, and ship new models into production
• You’ll work across all machine learning teams at Upstart, spanning from customer acquisition to credit underwriting to fraud detection and beyond
• Develop and execute strategies to (1) make more data available and usable for ML research, (2) accelerate model research & development workflows, and (3) deliver high-quality, low-latency model inference in production
• Establish and track success metrics to assess the impact of product initiatives, with a focus on ML efficiency/productivity, model and data quality, and online inference latency
• Make smart trade-offs to inform the ongoing product roadmap, prioritizing the features with the highest ROI and experimenting when necessary
• Collaborate closely with product managers, engineering, analytics, machine learning, operations, and other key stakeholders to align goals and streamline processes, ensuring cross-functional coordination and successful delivery of initiatives
• Leverage data-driven insights to make informed product decisions, identifying opportunities for optimization and testing hypotheses to improve key metrics