We are currently hiring for a mixed role thatis 70/30% ML Ops/Risk Data Scientist. Join us, and you will contribute tobuilding our decision and risk engine.
- Oversee and deploy ML pipelines, from development to production.
- Administer CI/CD pipelines, ensuring tests succeed and artifacts are properly stored.
- Monitor model performance metrics and set up alert systems for anomalies.
- Develop credit, fraud scoring and other predictive models.
- Engage with stakeholders to understand requirements and manage expectations.
- Document processes, and share knowledge and expertise.
- Manage project planning, execution, and progress tracking.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Proficiency in Python, SQL, and database management.
- Experience with Docker and deploying applications on cloud platforms such as AWS.
- Strong experience with CI/CD pipelines, automated testing, and deployment.
- Ability to use effectively monitoring tools and establish responsive alert systems.
- Robust documentation skills to clearly record processes and optimizations.
- Familiarity with SageMaker and other AWS services would be a significant advantage.
Benefits
- Competitive compensation.
- An agile culture with a flat hierarchy, offering the opportunity to tackle complex, real-world challenges.
- A team comprised of top-tier professionals with experience in leading consultancies and banks.
- The chance to play a pivotal role in building a data-driven culture.
