Lead Data Scientist

The Inside Job; Metropolitan Borough of Solihull; On-site; GBP 75,000 - 115,000; Full time

Job summary

The Inside Job is seeking a senior data science technical lead to shape and assure production‑grade ML across multiple initiatives. You will guide modelling, partner with stakeholders, and ensure scalable, reliable delivery aligned to business priorities.

Responsibilities include hands‑on leadership through the lifecycle, embedding standards, and mentoring data scientists while maintaining strong cross‑team collaboration with Data Architecture, ML & Data Engineering, and BI teams.

Qualifications

• Extensive experience delivering production‑grade data science solutions.
• Proven senior technical lead, reviewer, or sign‑off authority.
• Strong Python and SQL skills with practical ML knowledge.
• Experience building ML on cloud platforms (GCP/AWS/Azure).
• Ability to communicate complex technical decisions to non‑technical stakeholders.

Responsibilities

• Act as a technical lead for data science, guiding modelling approach and solution design across initiatives.
• Translate priority use cases into production‑ready data science solutions in collaboration with stakeholders.
• Provide hands‑on technical leadership across the data science lifecycle, from framing to deployment and optimisation.
• Define and embed technical standards for experimentation, validation, documentation, and reproducibility.
• Review and challenge technical designs, providing clear direction and sign‑off.

Skills

Python

SQL

Machine Learning

Leadership

Data Modelling

Time‑Series Forecasting

Communication

Tools

GCP

AWS

Azure

Job description

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