
Director, Machine Learning
- Austin, TX
- Permanent
- Full-time
- Leverage generative AI techniques to enhance fraud detection models, creating synthetic data for robust testing and model training.
- Incorporate generative AI into the machine learning strategy to introduce novel fraud detection methods and improve predictive accuracy.
- Utilize generative AI to simulate potential fraud scenarios, aiding in the development and refinement of fraud prevention solutions.
- Implement generative AI tools to facilitate communication and alignment between technical teams and business stakeholders, ensuring a shared understanding of goals.
- Define and drive the machine learning strategy for fraud prevention solutions.
- Align ML initiatives with Visa's broader business and technology objectives in the payments risk space.
- Lead the design, development, testing, and deployment of ML/DL models to detect and prevent payment fraud.
- Supervise model refresh cycles, experimentation, and continuous improvement.
- Partner with product managers, engineers, and business stakeholders to ensure alignment between technical and business goals.
- Work closely with support teams to troubleshoot production issues tied to models and pipelines.
- 10+ years of relevant work experience and a Bachelors degree, OR 13+ years of relevant work experience
- 12 or more years of work experience with a Bachelor's Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD
- Experience leading development, delivery and deployment of ML / DL models, feature engineering, model refresh, and experimentation.
- Experience leading product development & delivery of AI/ML solutions, applied to real-world problems
- Experience leading design and development of mission-critical, secure, reliable systems
- Excellent understanding of algorithms and data structures
- Excellent problem solving and analytics skills. Capable of forming and advocating an independent viewpoint
- Strong experience with agile methodologies
- Excel in partnering with Product leaders and technical product managers on requirements workshops, helping define joint product/technology roadmaps & driving prioritization
- Experience driving continuous improvements to processes/tools for better developer efficiency and productivity
- Demonstrated ability to drive measurable improvements across engineering, delivery and performance metrics
- Demonstrated success in leading high performing, multi-disciplinary and geographically distributed engineering teams. Demonstrated ability to hire, develop and retain high-caliber talent
- Must demonstrate longer-term strategic thinking and staying abreast with latest technologies to assess what's possible technically
- Strong collaboration and effective communication, with focus on win-win outcomes