- London, England
- £90000.00 - £110000.00 per annum
- Job Type
- Pierrick Rodriguez
An award winning and rapidly growing consultancy is currently looking for a Principle Data Science Consultant to join them in a strategic position.
You will be regarded as an SME and will be involved in a lot of the strategic decisions of the Data Science Branch.
In this role, you'll:
Collaborate with our clients to help shape their ML/AI strategy by understanding their businesses and objectives. You would typically be engaged with C level and/or senior stakeholders and navigate this complex landscape to align their ML/AI strategy with business objectives;
Demonstrate thought leadership by not just implementing clients' ML/AI strategy but also by advising them about the latest innovations in the market, helping them develop a well-rounded view;
Partner with and coach client Data Science teams to enable them to deliver high-value insights and models, and deliver sustained value through effective operationalisation;
When needed, roll up your sleeves to identify, design, and implement the tools clients need to deliver, operationalise, and monitor insights, enabling end-to-end MLOps;
Work closely with data/analytics engineering teams overseeing the building and operationalisation of ML pipelines, using agile and CI/CD methodologies.
- Use of ML algorithms & techniques (e.g., Regression, Decision Trees, Bayes, K-Means, PCA)
- Code and model optimisation techniques using Python/R/SQL
- Familiarity with machine learning frameworks & libraries (like Keras, PyTorch, scikit-learn)
- Experience of using one or more of the analytics cloud platforms such as Azure ML, Databricks, SageMaker, Vertex AI or DataIku (advantageous to have wider appreciation of available open-source frameworks like MLFlow)
- Implement scalable solution infrastructure by applying DevOps, automation, and continuous integration approaches in context of ML/AI implementations
- Experience creating and/or maintaining production software delivery pipelines using common CI/CD tools (GitHub Actions, Azure DevOps, Jenkins, CircleCI etc.)