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Senior/Lead Data Scientist -Credit Risk Modeling
Klarna · Milan
Pay
Not listed
Setting
On-site
At Klarna, our credit risk models sit at the heart of how we underwrite and price risk for millions of consumers globally. We're looking for a Lead Data Scientist to help shape the next generation of consumer-level credit scoring and portfolio valuation models. What you'll do As a Lead Data Scientist within credit risk modeling, you will shape Klarna's next-generation consumer-level credit scoring and portfolio valuation models. You'll design and maintain real-time PD (Probability of Default) models using statistical and ML approaches, integrating them into frameworks for underwriting and economic return optimization. You'll develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering. Collaborating with cross-functional teams, you'll translate modeling insights into strategic credit policies and business value, while mentoring junior team members and contributing to Klarna's long-term modeling vision. Who you are 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with explainability frameworks such as SHAP, LIME, PDP. Ability to communicate technical concepts clearly and influence cross-functional decisions. Familiarity with real-time modeling and current trends in ML and credit analytics. Awesome to have Hands-on experience using LLMs to extract features from unstructured data (e.g., customer communications, credit applications). Knowledge of integrating third-party credit bureau data into production models. Understanding of champion/challenger model frameworks and A/B testing infrastructure. Exposure to loan-level economic modeling, including cost-of-capital and loss metrics. Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist -Credit Risk Modeling
Klarna · London
Pay
$65k–230k
Setting
On-site
At Klarna, our credit risk models sit at the heart of how we underwrite and price risk for millions of consumers globally. We're looking for a Lead Data Scientist to help shape the next generation of consumer-level credit scoring and portfolio valuation models. What you'll do As a Lead Data Scientist within credit risk modeling, you will shape Klarna's next-generation consumer-level credit scoring and portfolio valuation models. You'll design and maintain real-time PD (Probability of Default) models using statistical and ML approaches, integrating them into frameworks for underwriting and economic return optimization. You'll develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering. Collaborating with cross-functional teams, you'll translate modeling insights into strategic credit policies and business value, while mentoring junior team members and contributing to Klarna's long-term modeling vision. Who you are 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with explainability frameworks such as SHAP, LIME, PDP. Ability to communicate technical concepts clearly and influence cross-functional decisions. Familiarity with real-time modeling and current trends in ML and credit analytics. Awesome to have Hands-on experience using LLMs to extract features from unstructured data (e.g., customer communications, credit applications). Knowledge of integrating third-party credit bureau data into production models. Understanding of champion/challenger model frameworks and A/B testing infrastructure. Exposure to loan-level economic modeling, including cost-of-capital and loss metrics. Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist - Open Banking
Klarna · Milan
Pay
Not listed
Setting
On-site
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!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist- Open Banking
Klarna · Stockholm
Pay
Not listed
Setting
On-site
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!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist - Open Banking
Klarna · London
Pay
$65k–220k
Setting
On-site
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!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior MLOps Engineer
Klarna · Stockholm
Pay
Not listed
Setting
On-site
As a Senior Engineer, you will work at the intersection of engineering and data science, building and productionizing machine learning pipelines that power Klarna's credit decisioning. You will take models from development through to production, ensuring pipelines are reliable, scalable, and ready for real-world use. Your day-to-day work will span writing Python to train models, building infrastructure to support the ML pipeline, and deploying models into production using tools such as tree-based models, AWS SageMaker. You will play a key part in scaling Klarna's in-house data science capabilities as we continue to grow our credit risk and fraud offerings. Who you are Strong experience with Python for data science and machine learning development Hands-on experience productionizing machine learning models and pipelines Practical experience with tree-based models Experience with AWS or comparable cloud infrastructure Understanding of MLOps practices for scaling models into production Experience collaborating with cross-functional teams Working proficiency and communication skills in verbal and written English Awesome to have Experience working in credit risk, fraud, or financial services Experience building data pipelines at scale within a larger data science organization Familiarity with model monitoring and observability tools Experience with CI/CD tools for ML deployment Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist - Credit
Klarna · London
Pay
$65k–220k
Setting
On-site
What you will do You will work on some of the most technically interesting modelling problems in fintech, training large transformer-based models on long sequences of real world transactional events. You will design tokenisation schemes for numerical, categorical, and temporal features, making deliberate decisions about vocabulary size, sequence length, and information compounding. Your work spans the full model lifecycle, from data preparation through to production and you will translate research decisions into systems that set the direction for how machine learning operates across Klarna. You will be part of a small, high ownership team where what you build has genuine impact on the products Klarna ships. Who you are Deep understanding of transformer architectures and sequence modelling, with the ability to reason through architectural tradeoffs Hands-on experience designing tokenisation schemes for heterogeneous feature types such as numerical, categorical, and temporal Proficiency in Python, PyTorch, SageMaker, and Airflow Experience owning the full model lifecycle, from training through to serving in production Comfortable working in a small, high ownership team on open ended technical problems Awesome to have Experience with Triton kernels or GPU-level optimisation Broader ML background spanning areas beyond deep learning Experience with large-scale transactional or financial data Background in ML infrastructure or MLOps Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site! klarna.com
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist -Credit
Klarna · Stockholm
Pay
Not listed
Setting
On-site
What you will do You will work on some of the most technically interesting modelling problems in fintech, training large transformer-based models on long sequences of real-world transactional events. You will design tokenisation schemes for numerical, categorical, and temporal features, making deliberate decisions about vocabulary size, sequence length, and information compounding. Your work spans the full model lifecycle, from data preparation through to production and you will translate research decisions into systems that set the direction for how machine learning operates across Klarna. You will be part of a small, high-ownership team where what you build has genuine impact on the products Klarna ships. Who you are Deep understanding of transformer architectures and sequence modelling, with the ability to reason through architectural tradeoffs Hands-on experience designing tokenisation schemes for heterogeneous feature types: numerical, categorical, and temporal Proficiency in Python, PyTorch, SageMaker, and Airflow Experience owning the full model lifecycle, from training through to serving in production Comfortable working in a small, high-ownership team on open-ended technical problems Awesome to have Experience with Triton kernels or GPU-level optimisation Broader ML background spanning areas beyond deep learning Experience with large-scale transactional or financial data Background in ML infrastructure or MLOps Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior/Lead Data Scientist -Credit
Klarna · Milan
Pay
Not listed
Setting
On-site
What you will do You will work on some of the most technically interesting modelling problems in fintech, training large transformer-based models on long sequences of real-world transactional events. You will design tokenisation schemes for numerical, categorical, and temporal features, making deliberate decisions about vocabulary size, sequence length, and information compounding. Your work spans the full model lifecycle from data preparation through to production and you will translate research decisions into systems that set the direction for how machine learning operates across Klarna. You will be part of a small, high-ownership team where what you build has genuine impact on the products Klarna ships. Who you are Deep understanding of transformer architectures and sequence modelling, with the ability to reason through architectural tradeoffs Hands-on experience designing tokenisation schemes for heterogeneous feature types such as numerical, categorical, and temporal Proficiency in Python, PyTorch, SageMaker, and Airflow Experience owning the full model lifecycle, from training through to serving in production Comfortable working in a small, high-ownership team on open-ended technical problems Awesome to have Experience with Triton kernels or GPU-level optimisation Broader ML background spanning areas beyond deep learning Experience with large-scale transactional or financial data Background in ML infrastructure or MLOps Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
Operational Risk Manager - Analytics
Klarna · Stockholm
Pay
Not listed
Setting
On-site
What you will do In this position, you will strengthen Klarna’s Operational Risk team by driving data-informed risk management across our global product portfolio. You will analyze structured and unstructured data to monitor risk performance, identify emerging patterns, and deliver actionable insights that support business and risk decisions. You will conduct independent control testing and process reviews to evaluate the effectiveness of risk frameworks, while contributing to regulatory reporting and governance. Working closely with stakeholders across product, engineering, data science, and operations, you will support continuous improvements to risk controls and help ensure Klarna remains resilient in a dynamic environment. Who you are • Minimum 5 years of experience in fintech, banking, or consulting with a focus on risk management • Proven experience performing independent data analysis and contributing to risk initiatives • Strong expertise in risk management and the ability to interpret complex datasets • Experience conducting control testing and process reviews within a risk or compliance environment • Understanding of regulatory requirements and experience supporting risk reporting processes • Strong communication skills with the ability to collaborate effectively across teams • Bachelor’s degree in Finance, Risk Management, Data Science, or a related field Awesome to have • Relevant professional certifications such as CFE, CRCMP, or similar • Experience working with data models, analytics techniques, or automated decision systems • Background in financial services, payments, or regulated industries • Ability to approach complex challenges and develop practical, scalable solutions • Experience working in fast-paced or high-growth environments Please include a CV in English Curious to learn more about Klarna and what it’s like to work here? Explore our career site!
Listed by Klarna for a position based in the United States. Employers on this board attest they are hiring domestically.
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