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Lead Data Scientist

2 months ago

United Kingdom Harnham Full time €100,000

Lead Data Scientist - Payments (12-month FTC) London
Lead and drive data-driven insights in payments analytics, shaping global commerce strategy for a dynamic tech start-up


Join as Lead Data Scientist, where you’ll play a pivotal role in shaping the payments landscape for a dynamic music tech leader. Handling over a billion transactions annually across a wide range of payment methods, their team excels in monitoring and reporting on payment performance, delivering critical insights that drive optimization strategies and support key business decisions.

Your expertise in data science will directly influence our global commerce strategy, ensuring seamless, efficient, and secure financial transactions for our growing user base.
In this role, you'll collaborate with a global team of top-tier data scientists, business managers, product managers, and engineers.


Develop a comprehensive understanding of the company's complex payments ecosystem and related data sources to derive insights into payment performance and identify opportunities for optimization.
Partner closely with Engineering, Product, Product Insights, and Business Analytics teams to align and drive strategic data initiatives.
Empower Data Access: Facilitate a self-service data environment within the Commerce Business team by utilising data modeling and visualization tools such as Looker, while also providing support for ad-hoc analysis requests as needed.
Performance Monitoring: Track and report on key performance indicators (KPIs) related to payment performance, delivering data-driven insights and recommendations on optimization strategies and potential challenges to the Commerce team.
Academic Background: Degree in Computer Science, Analytics Engineering, Mathematics, Statistics, Economics, or a similar quantitative field.
Demonstrated experience in leading teams and managing projects effectively.
Programming Expertise: Strong proficiency in Python or equivalent programming languages, along with relevant data science tools.
SQL & Data Tools: Advanced skills in SQL (Google BigQuery experience preferred) and familiarity with dashboard visualization platforms like Tableau, Looker, or Google Data Studio.