Translate broad business problems into sharp data science use cases, and craft use cases into product visions
Own machine learning products from vision to backlog; prioritizing features and defining minimum viable releases; maximizing the value your products generate, and the ROI of your pod
Guide Agile pods on continuous improvement, ensuring that the next sprint is delivered better than the previous
Work closely with stakeholders to identify, refine and (occasionally) reject opportunities to build machine learning products; collaborate with support functions such as risk, technology, model risk management and incorporate interfacing features
Facilitate the professional & technical development of your colleagues through mentorship and feedback
Anticipate resource needs as solutions move through the model lifecycle, scaling pods up and down as models are built, perform, degrade, and need to be rebuilt
Championing model development standards, industry best-practices and rigorous testing protocols to ensure model excellence
Self-direct, with the ability to identify meaningful work in down times and effectively prioritize in busy times
Drive value through product, feature & release prioritization, maximizing ROI & modelling velocity
Be an exceptional collaborator in a high-interaction environment

Minimum five years of experience delivering major data science projects in large, complex organizations
Strong communication, business acumen and stakeholder management competencies
Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices
Strong coding proficiency: python, R, SQL and / or Scala, cloud architecture
Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience
Familiarity with cloud solution architecture, Azure a plus
Master’s degree in data science, artificial intelligence, computer science or equivalent experience

Technical Product Owner

Key skills