Remote Risk & Data Analyst — BNPL Insights

تابي; España; Remote; EUR 45,000 - 65,000; Full time

Benefits offered by this job

Fully remote work

Flexible hours

Autonomy from day one

Stock options

Flexi Perks

Job summary

Tabby is seeking a Risk (Data) Analyst to shape and execute credit and fraud risk strategies across BNPL products. You’ll work with large datasets to identify trends, monitor portfolio health and support decisions across markets.

This is a remote role based in Spain with cross‑functional collaboration with data, product and finance teams. You should have 2–4 years in credit risk or fraud analytics, strong SQL and Python skills, and a business‑minded communicator capable of independent work in a

Qualifications

• 2–4 years of experience in credit risk, fraud analytics, or a related data‑driven role.
• Strong analytical skills and experience with SQL, Python or similar tools.
• Understanding of consumer lending, BNPL, or fintech risk models.
• Ability to work independently and in a fast‑paced, high‑growth environment.
• Clear communication and a business‑oriented mindset.

Responsibilities

• Analyze credit and fraud risk performance across customer segments and products.
• Develop and optimize risk strategies to improve approval rates and reduce losses.
• Monitor key risk indicators and portfolio trends; present insights to leadership.
• Contribute to the design and rollout of new risk models and policies.
• Collaborate with cross‑functional teams to support launches in new markets and verticals.
• Drive automation and efficiency in risk operations and reporting.

Skills

Analytical skills

SQL experience

Python experience

Independent worker

Business-minded

Communication

Tools

SQL

Python

Job description

Tabby is seeking a Risk (Data) Analyst to shape and execute credit and fraud risk strategies across BNPL products. You’ll work with large datasets to identify trends, monitor portfolio health and support decisions across markets.

This is a remote role based in Spain with cross‑functional collaboration with data, product and finance teams. You should have 2–4 years in credit risk or fraud analytics, strong SQL and Python skills, and a business‑minded communicator capable of independent work in a