ML Enablement Lead / Senior Applied Data Scientist

The ML Enablement Lead focuses on building ML capability and confidence within the business.

This role supports stakeholders who are new to machine learning and Databricks, helping them understand where ML adds value and how to use it effectively.

The emphasis is on coaching, skills transfer, and change adoption, rather than complex or academic modelling.

Key responsibilities:

• Work closely with business and technical stakeholders who are early in their ML journey
• Provide hands‑on coaching, mentoring, and guidance
• Support teams in building confidence with ML concepts and workflows
• Guide stakeholders through:
• Feature selection and model development
• Model evaluation and interpretation
• Focus on simple, practical, and valuable ML solutions
• Translate complex ML concepts into easy‑to‑understand workflows
• Create simple examples, templates, and learning materials
• Support workshops, training sessions, and informal learning
• Help stakeholders identify where ML:
• Adds real business value
• Is feasible within current skills and data
• Encourage pragmatic decision‑making over “perfect” solutions
• Experiment tracking
• Version control
• Basic deployment considerations
• Guide teams towards production‑ready thinking without overwhelming them
• Support behavioural and cultural change around ML adoption
• Build trust with non‑expert users
• Act as a supportive partner

Must‑have skills:

• Strong Python skills within the ML ecosystem
• Understanding of MLOps fundamentals
• Excellent communication, teaching, and coaching ability
• Ability to simplify complex topics
• Good business understanding and pragmatic mindset
• Ability to self‑start and work proactively
• Patience, coaching mindset, and focus on stakeholder needs

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