We are currently hiring for a mixed role that is 70/30% ML Ops/Risk Data Scientist. Join us, and you will contribute to building 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.

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