Vice President of Risk Management
3 weeks ago
We are a leading financial technology company dedicated to empowering consumers with flexible payment options and innovative shopping experiences. Our "buy now, pay later" platform enables millions of customers to make responsible purchases, manage payments, and drive growth for thousands of merchants.
Key Responsibilities:- Oversee the design, development, and deployment of machine learning models that power and enhance our financial platform.
- Drive the creation of scalable machine learning solutions for personalized recommendations, fraud detection, and credit risk assessment.
- Lead a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space.
- Design, build, and maintain scalable ML infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
- Collaborate with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
- Develop monitoring and alerting frameworks for machine learning models to ensure high performance, reliability, and minimal downtime.
- Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
- Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.
- Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field.
- At least 9+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
- Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
- Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
- Proficiency with Python is required, and experience with Golang is a plus.
- Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
- Experience working with relational databases, data warehouses, and using SQL to explore them.
- Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
- Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
- Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
- Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.
We value calculated risk-taking and deliver results. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, genetic information, pregnancy, or any other legally protected status.
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