Lead Data Scientist: Scale AI & Data Science Team (Bonus)

Harnham; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Performance-related bonus

Private healthcare and additional bene

Additional benefits package

Job summary

Harnham, a leading data and analytics recruitment firm, is recruiting a Lead Data Scientist for their London hybrid operation. You will head a team of data scientists, shape best practices, and drive production-ready ML solutions.

The role focuses on forecasting, segmentation, and propensity modelling, with strong stakeholder engagement and governance across the data science lifecycle. You will influence business outcomes through advanced analytics.

Qualifications

• Strong commercial experience in Data Science, Machine Learning, or Applied AI.
• Experience leading and developing Data Science teams.
• Advanced Python and SQL skills.
• Experience deploying models into production environments using MLOps practices.
• Strong communication skills with the ability to influence stakeholders.

Responsibilities

• Lead, mentor, and develop a team of Data Scientists and define best practices across the function.
• Design and deploy machine learning models across forecasting, customer segmentation, and propensity modelling.
• Own end-to-end model development including feature engineering, validation, deployment, and monitoring.
• Partner with Engineering and Product teams to build scalable, production-ready data science solutions.
• Translate analytical outputs into clear commercial recommendations for senior stakeholders.
• Drive the adoption of AI tooling and robust model governance across the data science lifecycle.

Skills

Data Science leadership

Python

SQL

Machine Learning

Stakeholder influence

Job description

Harnham, a leading data and analytics recruitment firm, is recruiting a Lead Data Scientist for their London hybrid operation. You will head a team of data scientists, shape best practices, and drive production-ready ML solutions.

The role focuses on forecasting, segmentation, and propensity modelling, with strong stakeholder engagement and governance across the data science lifecycle. You will influence business outcomes through advanced analytics.