Staff Data Scientist, Credit Karma

• Bachelor's or graduate degree in Computer Science, Software Engineering, or a related quantitative field (such as engineering, machine learning, data science, operations research, or economics) with a minimum of 8 years of industry experience
• Expertise in cloud computing, with hands-on experience using GPC or similar services
• Prior DS Ops or ML Ops experience, with a proven track record of success
• Expertise in monitoring and alerting tools, such as PagerDuty, with experience designing and managing alerting systems to ensure optimal model performance and data quality
• Ability to collaborate effectively across functions and with diverse stakeholders, including data scientists, engineers, analysts, and finance teams, in mid- or large-scale companies
• Strong communication skills, with the ability to articulate complex technical concepts and solutions to both technical and non-technical audiences

Desirable

• Join Credit Karma as a Staff Data Scientist - Data Science Ops, where you'll champion operational excellence across organizations, driving AI-powered innovation and collaboration
• With a deep understanding of data science and machine learning workflows, you'll build and lead by example, fostering a culture of operational excellence
• This highly cross-functional role requires strong partnerships with engineering, product, business, finance, and analytics teams, as well as mentorship skills, accountability, and the ability to navigate fast-paced environments with agility and poise
• Design and maintain systems, monitoring and alerting to detect anomalies and performance degradation of ML models; implement automation to streamline workflows
• Support with model development and deployment to production, ensuring seamless integration with existing infrastructure
• Develop and maintain dashboards and reports to provide insights into model performance and data quality
• Investigate and resolve model-related incidents, including data quality issues and prediction errors
• Design and implement cloud solutions (GCP) to containerize, deploy, version, and monitor data science models
• Collaborate and communicate effectively with data scientists, engineers and architects on model validation, testing, and quality assurance
• Document processes and best practices, and lead training sessions to upskill data scientists in Data Science Ops, promoting ops excellence and continuous learning