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Lead Data Scientist

Harnham
City of London
1 week ago
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Lead Data Scientist

Hybrid - London 1 day per week

Up to £85,000


About the Role

We are working with a high-growth performance marketing and technology company who are looking for a new Lead Data Scientist to join the team.


You'll be working at the intersection of data, technology, and marketing, you’ll lead the delivery of cutting-edge machine learning, optimisation, and analytics solutions that drive measurable business outcomes.


Reporting directly to the Director of Data, you’ll take ownership of high-impact projects across areas such as customer lifetime value, predictive modelling, bidding optimisation, and experimentation, whilst also acting as a data lead for major clients.


Initially hands-on, this role will evolve into a more strategic leadership position, with team management responsibilities (starting with three Data Scientists, growing to five within a year) expected within the first six months.


Key Responsibilities

  • Lead and deliver data science solutions across predictive modelling, optimisation, and experimentation.
  • Act as a strategic data partner to key clients, owning technical delivery and ensuring high-quality results.
  • Design and deploy machine learning models and optimisation algorithms in production environments.
  • Collaborate with engineering, marketing, and analytics teams to integrate data science into campaign strategy and tooling.
  • Mentor and guide junior data scientists, establishing best practices and scalable workflows.
  • Help grow and shape the data science team and its role within the wider business.


What We’re Looking For

  • Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS).
  • Experience with modern data warehouses (BigQuery, Snowflake, Redshift).
  • Proven experience in deploying machine learning models or optimisation algorithms into production.
  • Solid understanding of digital marketing concepts, platforms (e.g., Google Ads, Meta), and analytics tools.
  • Demonstrated experience across key use cases such as:
  • Customer Lifetime Value (CLV) modelling
  • Propensity scoring and lead prioritisation
  • Budget allocation and bidding optimisation
  • Experimentation, A/B testing, causal inference, MMM
  • Advanced analytics (e.g. marginal returns curves, supply-demand modelling)
  • Strong communication skills with the ability to simplify complex technical concepts for stakeholders.
  • Leadership potential with a willingness to coach and develop others.


Please note, that this role cannot offer sponsorship.

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