Description

Role Purpose:

· Drive the overall MLOps strategy along with other members of the Data Science & Insights (DS&I) team, while also collaborating with senior leadership to align strategies with broader organizational goals and objectives.

· Lead the development of innovative software tools to service both our Data Science solutions and wider business operations using relevant cutting-edge technologies (e.g. AWS, Git, Docker, Kubernetes, Jenkins)

· Ensure the architecture is continuously improved and evaluate emerging technologies and trends to maintain a competitive edge in the market

· Lead the development of tools/services that support critical operations such as release management, source code management, CI/CD pipelines, automation, serving ML models to production environments and many other key operations while also overseeing the integration of these solutions into our broader technology ecosystem.

· Champion ML model-governance by establishing full end-to-end lifecycle governance framework to ensure models are monitored, refreshed and performing at optimal levels over time.

· Collaborate closely with key stakeholders across various business functions, including Product & Technology (P&T), IT, and Developer Experience (DX) teams, to develop and prioritize a strategic Data Science DevOps roadmap that aligns with organizational objectives and drives innovation.

· Mentor and coach team members, providing guidance, support, and expertise on advanced MLOps practices, while also serving as a point of escalation for complex technical challenges and issues

· Act as a strategic advisor to senior leadership, providing insights, recommendations, and strategic direction on Data Science MLOps initiatives, while also championing a culture of continuous learning, growth, and innovation within the organization.

Reporting to: Director of Data Science & Insights

Head of Machine Learning Operations

Description

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