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Senior Product Manager
AI/ML, Fraud Solutions
Confirmed live in the last 24 hours
San Francisco, CA, USA
Experience Level
Desired Skills
Data Analysis
Data Science
  • Minimum 5 years of experience in product management within the AI/ML domain, preferably computer vision and/or fraud/risk prevention domain
  • Master's degree in business, computer science or any related field
  • Track record of working with AI/ML/Data Science and Engineering teams to define, build and maintain highly scalable, mission-critical systems
  • Full stack knowledge of building AI platform, microservice architecture, Cloud (AWS) architecture, ML infrastructure and architecture, risk and fraud modeling and controls
  • High-level understanding of machine learning concepts and general practices
  • Experience with rapid experimentation, including definition of hypothesis, success metrics, A/B Testing and data analysis
  • Proficiency in data analysis using SQL, Tableau, Redshift, and Python
  • Ability to work effectively within a team and build positive relationships cross-functionally
  • Self-driven and highly motivated with a strong attention to accuracy and detail
  • Excellent troubleshooting, analytical and problem-solving abilities with a commitment to finding the root cause of issues
  • Good understanding of AI & ML ecosystem and products in the market
  • Strong written and verbal communication skills to help drive strategy and influence stakeholder teams
  • Experience leading a cross- functional team in an agile environment
  • Open to learn, develop, change, experiment, and have fun!
  • Manage products throughout their entire lifecycle
  • Own the strategy, planning and execution of fraud solutions for the best-in-class AI-driven biometrics identity verification platform
  • Lead the prioritization and development of your product's roadmap to deliver value to our customers and the business
  • Own and write comprehensive product requirements to build the AI & ML identity products and fraud detection solutions across industries use cases which empowers the team to continuously improve our core technology including ID verification, facial recognition, etc
  • Develop hypothesis, success metrics & KPIs, run experiments, analyze data, and make improvements to core machine learning models
  • Partner closely with analytics and engineering teams, and interface with cross functional stakeholders e.g. executives, sales, product, marketing, legal, and customer success teams
  • Regularly meet and work with our B2B customers to gather feedback and refine product strategy
  • Define best practices to help build a data driven culture across the company
Incode Technologies

51-200 employees

Powering the future of omnichannel biometric identity
Company Overview
Powering the future of omnichannel biometric identity