Credit Risk Analytics Specialist — Remote

Tabeo; Greater London; On-site; GBP 60,000 - 85,000; Full time

Benefits offered by this job

Remote-first

Training budget

Home-office setup

Private medical cover

Electric car scheme

24 days leave + birthday off

Parental leave

Pension scheme

Team trips

Job summary

Tabeo is seeking an analyst to join our data team with a focus on credit risk. The role involves managing and optimising credit risk and fraud strategies for lending operations and driving improvements to credit assessments.

You will split your time between exploring data tasks, coding, and presenting insights. The ideal candidate communicates clearly, works independently, and thrives in a fast-growing environment.

Qualifications

• Bachelor's degree in mathematics, statistics, or related field.
• At least 4 years of credit risk analysis experience, focused on consumer lending.
• Expertise in underwriting performance and model functions.
• Ability to build models with statistical tools (Python, R, SAS or similar).
• Strong SQL skills for data extraction and manipulation.
• Independent, able to own complex projects.
• Familiarity with BigQuery, DBT and open banking platforms is an advantage.
• Experience in counterparty risk analysis is a plus.

Responsibilities

• Manage and optimise credit risk and fraud strategies for lending operations.
• Own performance and projects; drive improvements to credit assessments.
• Balance task exploration, coding, and presenting insights to stakeholders.
• Explain compelling data insights to non-technical audiences.
• Automate repeating tasks to free time for high-impact work.

Skills

Python

SQL

Statistics

Data modeling

Open banking

Counterparty risk

Education

Bachelor's degree

Tools

R

SAS

BigQuery

DBT

Job description

Tabeo is seeking an analyst to join our data team with a focus on credit risk. The role involves managing and optimising credit risk and fraud strategies for lending operations and driving improvements to credit assessments.

You will split your time between exploring data tasks, coding, and presenting insights. The ideal candidate communicates clearly, works independently, and thrives in a fast-growing environment.