Klarna logo

Senior/Lead Data Scientist - Open Banking

Klarna

London, England, United KingdomFull-time$65–220K/yrPosted 1mo agoVerified open 3 days ago

Most applications go out cold — see where you stand first. No sign-up to start.

At a glance

Compensation
$65–220K/yr
Location
London, England, United Kingdom
Schedule
Full-time
Work Authorization
Not specified

Job overview

Klarna is hiring a Senior/Lead Data Scientist - Open Banking. The Senior Data Scientist on Klarna's Open Banking team builds the analytical foundation that converts raw bank account data into actionable insights for fraud prevention and underwriting, engineers feature engineering across cash flows, develops classification models for affordability and fraud, owns model lifecycle through production, monitors performance via dashboards, and partners with Credit Modeling and Fraud teams.

Key focus areas include Build analytical foundation converting raw bank data into actionable insight, Engage in feature engineering across cash flow data for affordability modeling, and Develop machine learning models estimating probability of default and fraud scores.

Successful candidates bring Experience Building And Deploying Machine Learning Models End To End and CV In English. Important skills include Feature Engineering, Machine Learning Models, Python, SQL, AWS, and Classification Modeling Techniques. Preferred (not required): Open Banking Data, Affordability Modeling, Databricks, and Datadog.

Skills & qualifications

RequiredNice to have

Skills

Feature EngineeringMachine Learning ModelsPythonSQLAWSClassification Modeling TechniquesCommunicationOwnership-Driven MindsetOpen Banking DataAffordability ModelingDatabricksDatadogUnderwritingCredit RiskFraud Detection

Qualifications

Experience Building and Deploying Machine Learning Models End to EndCV in EnglishExperience With Transactional or Financial Data

Full job description

What you will do

As a Senior Data Scientist within our Open Banking team, you will build the analytical foundation that turns raw bank account data into reliable, actionable insight for fraud prevention and underwriting decisions. You will engage in feature engineering across incoming and outgoing cash flows to model affordability, and develop machine learning models that estimate probability of default and produce fraud scorecards. You will own the full lifecycle of these models, from raw data through to production deployment, working closely with engineering to operationalize your work at scale. You will also help monitor model performance, impact, and acceptance rates through dashboards you help build, and you will partner closely with the Credit Modeling and Fraud teams to align on shared goals and infrastructure.

Who you are

  • Experience building and deploying machine learning models end to end, from raw data to production

  • Strong feature engineering skills, ideally with transactional or financial data

  • Proficient in Python and SQL, with experience working in AWS environments

  • Solid understanding of classification modeling techniques for risk or fraud use cases

  • Comfortable partnering closely with engineering teams to bring models into production

  • Strong communication skills, with the ability to work cross-functionally with Credit Modeling and Fraud teams

  • A curious, ownership-driven mindset, comfortable building infrastructure and processes from scratch

Awesome to have

  • Experience with open banking data or affordability modeling

  • Familiarity with building dashboards for model monitoring, ideally with tools like Databricks

  • Experience with monitoring and observability tools such as Datadog

  • Background in underwriting, credit risk, or fraud detection use cases

Please include a CV in English

Curious to learn more about Klarna and what it's like to work here? Explore our career site !

You've read the whole posting — now see how you match it.