Machine Learning Maturity: 4-week Assessment

The assessment follows BJSS' evaluation methodology which examines the six pillars of operating machine learning workloads (MLOps) in production, giving you actionable insights into your level of maturity across 30 criteria:

• Ways of Working: Are your teams following best practice and able to achieve their objectives? • Data & Features: Is your data sufficient, useful and accessible? • Model: Are your models robust, maintainable and performant? • ML Pipelines & Platform: What level of automation can your models rely on? • Monitoring & Operations: What solutions do you have in place to keep track of models' accuracy over time? • Security & Governance: What processes and tools do you have in place to manage access to data and secure your platform?

Focusing on those key aspects around people, processes and technology, the BJSS Machine Learning maturity assessment appraises your current state and compares it to your ambitions. The assessment is conducted in a fully collaborative and transparent way - thus enabling you to review findings as they are discovered - and it delivers a gap analysis identifying clear areas requiring investment and attention through:

• A clear explanation of your current maturity score against each of the six Machine Learning maturity pillars • A recommended level of maturity aligned to your business strategy • Actionable and prioritised recommendations for remediations to be implemented to help move you up the maturity curve.

BJSS Data Science and Data Engineering experts come with relevant industry expertise, engineering discipline, and deep knowledge of Azure ML, Databricks on Azure and other Azure services required to build, optimize, and scale production-ready ML models that integrate with key business processes and systems. Working with them over the assessment will help you gain an in depth understanding of the root causes for the challenges you've faced around data science and machine learning.