Lead Data Scientist
Summary
The Lead Data Scientist oversees end-to-end ML/data science projects, ensuring scalable, production-ready solutions aligned with business goals. Core work includes technical leadership, model deployment, standards enforcement, and mentoring across Python/SQL, cloud platforms (AWS/GCP/Azure), and ML techniques like time-series forecasting.
This role exists to provide technical leadership and assurance across data science, ensuring machine learning solutions are designed, built, and operated to a high and consistent technical standard. The role focuses on enabling scalable, reliable delivery of data science solutions aligned to business priorities defined elsewhere.
WHAT YOU'LL BE DOING:
- Acting as a technical lead for data science, guiding modelling approach and solution design across multiple initiatives.
- Working closely with business stakeholders to translate priority use cases into technically sound, production‑ready data science solutions.
- Providing hands‑on technical leadership across the data science lifecycle, from problem framing and modelling through deployment and ongoing optimisation.
- Defining and embedding technical standards and best practices for experimentation, validation, documentation, and reproducibility.
- Reviewing and challenging technical designs and implementations, providing clear technical direction and sign‑off.
- Supporting and mentoring data scientists on complex technical challenges.
- Partnering with Data Architecture, ML & Data Engineering, and BI teams to ensure solutions are scalable, robust, and production‑ready.
- Evaluating new techniques and tools, guiding their pragmatic adoption.
- Communicating technical assumptions, risks, and trade‑offs clearly to technical and non‑technical stakeholders.
Accountable for:
- The technical quality and consistency of data science solutions delivered within assigned domains.
- Ensuring solutions meet agreed performance, scalability, reliability, and maintainability standards.
- Consistent application of data science standards, reducing delivery risk and technical debt.
- Providing ongoing technical assurance that solutions remain fit for production as usage and complexity increase.
- Maintaining strong technical partnerships with stakeholders as a trusted advisor.
- Raising the overall technical maturity of data science within the organisation
WHAT YOU'LL NEED:
Essential Criteria:
- Extensive experience delivering production‑grade, commercially impactful data science solutions, gained in a data science or machine learning roles.
- Proven experience operating as a senior technical lead, reviewer, or technical sign‑off authority.
- Strong experience building ML solutions on cloud platforms (GCP, AWS, or Azure).
- Advanced expertise in Python and SQL.
- Deep applied knowledge of machine learning techniques, including regression, classification, clustering, and time‑series forecasting.
- Experience supporting production deployment and lifecycle management of ML models.
- Strong understanding of data warehousing, data modelling, and modern data architecture.
- Excellent communication skills, able to explain technical decisions clearly to non‑technical stakeholders.
Preferred Skills:
- Experience with recommender systems or personalisation use cases.
- Familiarity with MLOps concepts and production ML practices.
- Demonstrated ability to raise technical standards through influence rather than authority.
- Experience in an e‑commerce or retail environment.
CLOSING DATE: 14th August
