Lead Data Scientist - Payments (12-month FTC)
London
Up to £100,000
Lead and drive data-driven insights in payments analytics, shaping global commerce strategy for a dynamic tech start-up!
Company:
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.
Role:
Key Responsibilities:
Gain Expertise:
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.
Cross-Functional Collaboration:
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.
System Oversight:
Manage the development and upkeep of the payments alerting system, ensuring the Commerce Operations team is promptly notified of any payments-related incidents requiring immediate action.
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.
Hands-On Leadership:
Although this is a management role, you will be an integral part of a small team, necessitating a significant amount of individual contributor work.
Requirements:
Academic Background:
Degree in Computer Science, Analytics Engineering, Mathematics, Statistics, Economics, or a similar quantitative field.
Leadership & Management:
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.
How to Apply:
Please register your interest by sending your CV to Luc Simpson-Kent via the Apply link on this page.
Desired Skills and Experience
Payments, Data Science, Python