Senior Data Scientist

• Take full ownership of data-driven analyses, independently deriving actionable recommendations to maximise business value
• Develop and apply advanced statistical methods (regression models, time series analyses, ML/AI algorithms) and translate results into clear, compelling business insights
• Design and maintain robust end-to-end ML pipelines (data, features, models, scoring), including testing, versioning, documentation, and MLOps standards such as CI/CD, model registry, monitoring, data-quality checks, and incident handling
• Collaborate closely with stakeholders and management
• Own the SmartRisk Engine within Credit & Risk Management: feature strategy, training/retraining, calibration, backtesting, drift monitoring, and explainability via SHAP/Reason Codes
• Build data-driven use cases such as loss databases, early-warning systems, limit/exposure steering, clustering, and portfolio insights
• Develop new cloud-based Data Science solutions, primarily in Python and SQL, to drive measurable business value
• Ideally, you bring knowledge in credit risk (e.g., PD, EAD, LGD, rating, IFRS 9/ECL) and experience with SAP and Power BI
• Mentor and guide other Data Scientists, encourage innovative thinking, and actively support the team’s professional growth, * Full ownership from day one. You will be the one owning the engine, not coordinating from the sidelines.
• Close collaboration with senior leadership and visibility to C-level stakeholders.
• An international, diverse environment spanning HQ strategy teams to field sales organisations across European markets.
• Flexible hybrid working, company health management, Jobrad eBike leasing, and parent-child offices

Do you have experience in SQL?, * 5-8 years of experience in Data Science and Machine Learning, confidently applying statistical methods, regression models, time series analyses, classical ML, and modern AI algorithms

• Highly proficient in Python and SQL, independently developing value-adding, cloud-based solutions, including Generative AI use cases such as LLMs, RAG systems, and “talk-to-your-data” interfaces (AI agents or chat interfaces)
• Proven track record building robust end-to-end ML pipelines and maintaining MLOps standards (CI/CD, model registry, monitoring, quality checks)
• Hands-on ownership of risk models such as the SmartRisk Engine (feature strategy, training, calibration, backtesting) and explainability methods like SHAP or Reason Codes
• Domain knowledge in credit risk (PD, EAD, LGD, rating processes, IFRS 9/ECL) and experience with SAP and Power BI is an advantage
• You communicate clearly, presenting complex analytical results to business units, IT, and management and translating them into actionable results
• Experience mentoring and guiding other Data Scientists is an advantage

Please note that this position is based close to Düsseldorf. At least three days per week on-site are preferred.

As a key growth accelerator, A11 partners with Europe’s most ambitious startups and scaleups, corporates and SMBs to connect them with top-tier talent ready to make an impact.

We’re looking for a Senior Data Scientist (m/f/d) in Credit & Risk Management to take ownership of the Smart Risk engine at the core of one of Europe’s leading B2B mobility and payment platforms.

Our partner company serves customers across more than 50 countries. Built on over 90 years of continuous growth and innovation, the company has evolved into a market-leading platform with around 2,700 employees, processing €19 billion in transaction volume. As the business enters its next phase of development, it is investing heavily in data, AI, and technology-enabled commercial excellence to strengthen its market position and unlock new opportunities at scale.

In this role, you will own the Smart Risk Engine end to end. From feature strategy and model training to calibration, backtesting, drift monitoring, and explainability. This is a hands-on role, which means you will design data-driven use cases such as early-warning systems, loss databases, limit and exposure steering, and portfolio insights that directly shape how credit risk is managed across the platform.

With direct exposure to senior decision makers, real influence over how risk is quantified and managed at scale, this role offers a rare opportunity to shape a business critical capability from the inside.