What are the responsibilities and job description for the Machine Learning Scientist - Staff level position at Visa?
Responsibilities:
- Design, develop, and deploy machine learning and statistical models for large-scale, real-time and batch payment systems.
- Apply advanced techniques in supervised, unsupervised, and semi-supervised learning, including deep learning, anomaly detection, and graph-based models.
- Partner with data engineers and platform teams to build scalable ML pipelines for training, inference, monitoring, and retraining.
- Collaborate with product managers and domain experts to define ML-driven solutions aligned with business objectives.
- Conduct exploratory data analysis, feature engineering, and model experimentation using large, complex datasets.
- Evaluate model performance using robust offline metrics and online experimentation (A/B testing).
- Drive improvements in model accuracy, latency, explain ability, robustness, and fairness.
- Contribute to architectural decisions related to ML platforms, model serving, and real-time decision systems.
- Mentor junior scientists and engineers in ML best practices, experimentation rigor, and applied research.
- Stay current with emerging research and apply relevant advances in machine learning, AI, and data science to production systems.
- Translate ambiguous business problems into well-defined ML formulations and solution approaches.
- Own the end-to-end ML lifecycle: problem definition, data preparation, modeling, evaluation, deployment, and monitoring.
- Produce high-quality technical documentation explaining model design, assumptions, and trade-offs.
- Collaborate across engineering, product, architecture, risk, and operations teams to ensure successful adoption of ML solutions.
- Provide technical leadership in model reviews, experimentation design, and production readiness assessments.
- Support production models, including troubleshooting performance degradation and participating in on-call rotations as needed.
- Ensure models meet Visa’s standards for security, privacy, compliance, and ethical AI.
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.