About the role
Responsible for leading advanced applied science initiatives that drive innovation, optimise business outcomes, and expand the capabilities of data-driven products and services. This role requires strategic oversight, technical excellence, and the ability to translate scientific advancements into real-world applications. It involves cross-functional collaboration, mentoring, and execution of complex machine learning and artificial intelligence solutions.
Responsibilities:
- Lead a team of applied scientists and machine learning engineers in developing and deploying advanced models and algorithms.
- Drive the technical vision, research agenda, and roadmap for applied science initiatives aligned with business priorities.
- Oversee experimentation, evaluation, and deployment of machine learning models into production environments.
- Collaborate with Product, Engineering, and Data teams to integrate models into scalable systems.
- Champion best practices in scientific rigour, experimentation, reproducibility, and responsible AI.
- Mentor team members and foster a high-performance culture grounded in innovation and continuous learning.
- Monitor project progress, remove blockers, and ensure delivery of high-impact outcomes on time and within scope.
- Represent the applied science function in executive and strategic planning discussions.
Requirements:
- PhD or Master's degree in Machine Learning, Computer Science, Statistics, or a related field.
- 16+ years of experience in applied science or machine learning roles, including at least 3 years in a management role.
- Proven experience building and deploying ML models in production systems.
- Deep understanding of supervised, unsupervised, and deep learning techniques.
- Strong coding skills in Python and proficiency with ML frameworks such as PyTorch or TensorFlow.
- Excellent communication, stakeholder management, and cross-functional leadership skills.
- Experience managing complex technical projects and delivering measurable business impact.