• Demonstrated ability to communicate technical concepts to a non-technical audience.
• Ability to take a business problem and design a technical solution to tackle the problem.
• Strong grasp of fundamental concepts of statistics and probability.
• Solid understanding of main machine learning algorithms for supervised and unsupervised learning including how they work, their advantages, limitations and uses.
• Strong Python and SQL skills.
• Experience of working with machine learning frameworks such as tensorflow, scikit-learn and torch.
• Familiarity with Cloud ML tools and an understanding of principles of ML model productionization.
• Familiarity with version control (e.g. git) and with agile working practices.

• Collaborative and proactive
• Strong attention to detail, problem-solving and critical thinking
• Logical and methodical
• Articulate, persuasive and commercially aware
• Excellent communication (verbal and written)

It would be great if you have (or are excited to gain)…

• Commercial or Academic experience with Computer Vision, NLP or reinforcement learning.
• Experience in consultancy.
• Commercial experience of MLOPs .
• Experience of working with Google Cloud.