Senior Data Scientist (Machine Learning)

Job title: Senior Data Scientist (Machine Learning)

Company: Danske Bank


Job description: Job Category: Analysis and ResearchJob Description:Are you ready to redefine how customers experience banking through data-driven insights and personalization? At Danske Bank, we’re looking for a Senior Data Scientist to drive the development of machine learning models that power smarter engagement, proactive retention, and tailored financial advice towards our customers.This role is an unique opportunity to make a direct impact on millions of customers by turning behavioral data into predictive insights that shape how we communicate, serve, and grow our relationships.👥 Who are weThe Commercial Data Science CoE is a diverse team of Data Scientists, ML Engineers and MLOps Engineers with various educational and cultural backgrounds. We are responsible for applying AI in Danske Bank’s customer facing solutions, ranging anywhere from ML models used for personalisation and marketing optimisation to chatbots and advisor assistants.We pride ourselves on being at the forefront of the latest technology and research identifying use cases where AI can be applied to create value for customers and the bank.💼 What You’ll DoAs a key player in our Customer AI team, you’ll lead the development of high-impact models that enable our marketing and CRM functions to deliver relevant, timely, and effective customer interactions:

• Build propensity models to predict likelihood of product uptake (e.g., mortgage, investment, credit card)
• Design customer segmentation frameworks for targeting, lifecycle management, and personalization
• Develop churn prediction models to proactively identify at-risk customers and trigger retention actions
• Estimate and optimize customer lifetime value (CLV) to inform product prioritization, pricing, and targeting
• Apply uplift modeling and causal inference to evaluate marketing treatment effects and campaign ROI
• Collaborate with Marketing, Digital, and Personal Banking teams to activate models in real-time journeys
• Work with Data Engineering to improve the customer data foundation and feature store
• Contribute to our model governance and risk management standards in compliance with banking regulation

📊 What You Bring

• 5+ years of experience in data science or machine learning, ideally within financial services or customer analytics
• Deep understanding of predictive modeling techniques and experience applying them to customer behavior
• Hands-on expertise in Python (e.g., pandas, scikit-learn, XGBoost), SQL, and cloud-based data platforms
• Experience building and validating models using customer transactional, behavioral, and channel data
• Strong business acumen in retail banking: understanding of financial products, customer lifecycles, and marketing dynamics
• Ability to communicate model insights clearly to stakeholders across both technical and non-technical teams
• Familiarity with GDPR, model explainability, and regulatory compliance in model development

🌟 Nice to Have

• Experience with marketing automation or personalization platforms (e.g., Salesforce, Adobe, Pega)
• Familiarity with uplift modeling, causal ML, or reinforcement learning for offer optimization
• Experience deploying models into production using MLOps tools (e.g., MLflow, Airflow, Docker, Azure ML)
• Knowledge of CLM (customer lifecycle management), cross-sell strategy, or omni-channel personalization

🚀 Why Join Us?

• Help shape how the bank interacts with its customers using advanced analytics and AI
• Join a growing, ambitious AI team working at the core of our digital transformation
• Collaborate across an agile and business-oriented organization
• Working in our new HQ with great facilities

📩 Interested?Apply now or reach out to Rasmus Gansted Brink – RBRI@danskebank.dk for more information. Let’s build the future of AI together.
First interviews will start up end of June, so don’t hold back!

Expected salary:

Location: København

Job date: Mon, 09 Jun 2025 03:21:59 GMT

To help us track our recruitment effort, please indicate in your email/cover letter where (jobsnear.pro) you saw this job posting.Thanks&Good Luck