Data Science Specialist

• Optimize Operations: Assess and refine current delivery processes, governance, and operating models to reduce friction and boost collaboration across cross-functional teams (Product, Content, and Software).
• Strategic Roadmap: Review delivery roadmaps, optimize short-term resourcing, and help construct a medium-term team development plan for 2027 P&L planning.
• Standards & Best Practices: Refine end-to-end standards for data science development, testing, and deployment to balance technical rigor with commercial delivery.
• Team & Capability Design: Collaborate with leadership to define future team structures, role designs, and hiring strategies for permanent talent and contractors.
• Mentorship: Coach existing team members through process updates and modern cross-functional ways of working.

• Data Science & ML Expertise: Strong academic background (e.g., Master’s degree in Data Science or a scientific discipline with significant ML focus) alongside practical data science experience.
• Software Engineering Discipline: Proven ability to write production-grade Python code, enforce unit testing, exception handling, and logging, and manage full deployment without handing prototypes off to separate teams.
• Operations & Strategy Track Record: Experience assessing and improving operating models, delivery processes, and team effectiveness within data-driven environments.

Technical Stack:

• Core: Python, Git
• Cloud & DevOps: AWS, Docker, EKS, Kubernetes awareness, and automated CI/CD deployment pipelines
• Concepts: Configuration management (separating configuration from code), dimensionality reduction, and prompt engineering/LLMs
• Communication: Exceptional written and verbal skills, with a track record of producing clear technical documentation and aligning cross-functional stakeholders.