About the role
You will be involved in a financial project focused on delivering modern data and analytics solutions, supporting the development and operationalization of Machine Learning capabilities in a cloud environment. You will act as a bridge between business stakeholders and development teams, ensuring that business needs are translated into high-quality IT solutions and clear functional as well as non-functional requirements.
Do you fit?
Minimum 5 years of experience in analysis
Experience in AWS SageMaker implementation, preferably in direct collaboration with data scientists
Excellent communication and stakeholder management abilities, including experience working with business users
Familiarity with Machine Learning concepts, CI/CD pipelines, and Big Data technologies
Practical knowledge of SQL and Python
Ability to quickly understand new technologies at a high level and ask the right questions to drive effective solutions
Experience working with complex end-to-end processes and systems
Experience implementing model monitoring and MLOps capabilities
Knowledge of integrating AWS SageMaker model outputs with cloud, hybrid, and on-premises environments
Advanced understanding of Machine Learning algorithms
Experience with Spark and/or Scala
What you'll own
Helping to design advanced solutions around data and analytics
Working closely together with stakeholders to understand the expected outcome and elicit business features
Managing delivery dependencies towards other teams and organization units
Working in an Agile environment as an integral part of the cross-functional agile delivery team
Working alongside data scientists to implement and optimize AWS SageMaker capabilities for end user
Sound like you?
Negotiable · Jit Team
On Jit Team's website · ~2 minutes
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