Data Analyst (Operations Analytics)

TL;DR

Data Analyst (Operations Analytics): Building and optimizing operational reporting and automation solutions for a fast-growing fintech platform with an accent on Python-based data analysis and SQL-driven insights. Focus on identifying operational bottlenecks, supporting US expansion, and developing proof-of-concept automations to improve scalability and cost-to-serve.

Location: Must be based in London, UK (Hybrid role with office attendance required Tuesday-Thursday).

Company

hirify.global is a profitable, unicorn-status fintech company rebuilding consumer finance products like loans, credit cards, and car finance to provide faster, more efficient credit access.

What you will do

• Build performance dashboards and reporting baselines for new and scaling products.
• Analyze operational workflows to identify and resolve bottlenecks and inefficiencies.
• Use Python and SQL to investigate operational performance, cost-to-serve, and commercial impact.
• Develop proof-of-concept automations using Python, APIs, and LLMs to reduce manual effort.
• Support cross-functional analysis across QA, fraud, AML, and customer support operations.
• Translate ambiguous operational challenges into clear analytical outputs and actionable recommendations.

Requirements

• Minimum 1 year of experience in an analytics, data, or technical operations role.
• Strong proficiency in Python for data analysis and automation.
• Advanced SQL skills for querying, joining, and transforming large datasets.
• Solid understanding of basic statistics and data science principles.
• Strong analytical problem-solving skills and ability to work in fast-paced environments.
• Excellent communication skills for presenting findings to senior stakeholders.

Nice to have

• Experience with dbt or modern analytics engineering workflows.
• Experience building data pipelines or integrating with REST APIs.
• Exposure to LLMs, prompt engineering, or AI engineering workflows.
• Understanding of operational workflows like fraud, disputes, or workforce planning.

Culture & Benefits

• Best-in-class compensation package including equity.
• Hybrid work model with flexibility to work from home on Mondays and Fridays.
• Fresh, healthy lunches prepared by in-house chefs in the office Tuesday-Thursday.
• Private health insurance coverage for physical and mental well-being.
• Inclusive and open workspace culture in London.

Hiring process

• Screening call with Python questions.
• Live technical Python interview.
• Case study interview.
• Final culture-add interviews.