Payments Data Science Lead
2 months ago
Job Title: Lead Payments Data Scientist
Company: Harnham
Job Type: Full-time
Location: Remote
Job Description:
Overview:
Harnham is seeking a highly skilled Lead Payments Data Scientist to join our team. As a Lead Payments Data Scientist, you will be responsible for leading and driving data-driven insights in payments analytics, shaping global commerce strategy for a dynamic tech start-up.
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 utilizing 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.
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