What You’ll Do:
- 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
Minimum Basic Requirement:
- 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
Preferred Qualifications:
- Strong programming skills in SQL, Python, Ruby, and Bash, with a solid understanding of Linux and experience with frameworks like scikit-learn, Keras, PyTorch, and TensorFlow
- Proficiency with DS / ML Ops frameworks like Airflow, Kubeflow, MLFlow or similar
- Cloud solution design and implementation expertise, with experience building DS / ML Ops pipelines on GCP
Benefits at Credit Karma includes:
- Medical and Dental Coverage
- Retirement Plan
- Commuter Benefits
- Wellness perks
- Paid Time Off (Vacation, Sick, Baby Bonding, Cultural Observance, & More)
- Education Perks
- Paid Gift Week in December
Equal Employment Opportunity:
Credit Karma is proud to be an Equal Employment Opportunity Employer. We welcome all candidates without regard to race, color, religion, age, marital status, sex (including pregnancy, childbirth, or related medical condition), sexual orientation, gender identity or gender expression, national origin, veteran or military status, disability (physical or mental), genetic information or other protected characteristic. We prohibit discrimination of any kind and operate in compliance with applicable fair chance laws.
Credit Karma is also committed to a diverse and inclusive work environment because it is the right thing to do. We believe that such an environment advances long-term professional growth, creates a robust business, and supports our mission of championing financial progress for everyone. We offer generous benefits and perks with a single eye to nourishing an inclusive environment that recognizes the contributions of all and fosters diversity by supporting our internal Employee Resource Groups. We’ve worked hard to build an intensely collaborative and creative environment, a diverse and inclusive employee culture, and the opportunity for professional growth. As part of the Credit Karma team, your voice will be heard, your contributions will matter, and your unique background and experiences will be celebrated.
Please contact if you are interested in employment with Credit Karma and need special assistance or an accommodation to either apply or interview for a specific role.
Privacy Policies:
Credit Karma is strongly committed to protecting personal data. Please take a look below to review our privacy policies:
