Lead Data Scientist

About IXOPAY

IXOPAY is the enterprise-grade global payment infrastructure platform built for the era of agentic commerce.

We equip merchants and enterprises with AI-driven intelligence, payment orchestration, advanced tokenization, and the tools to optimize every stage of the payments journey.

About IXOPAY

IXOPAY is the enterprise-grade global payment infrastructure platform built for the era of agentic commerce.

We equip merchants and enterprises with AI-driven intelligence, payment orchestration, advanced tokenization, and the tools to optimize every stage of the payments journey.

From intelligent routing and compliance to customizable modules and enterprise-scale orchestration, IXOPAY helps businesses integrate faster, improve payment performance, and expand globally with confidence.

At IXOPAY, our people are our greatest strength. Our collaborative culture is built on shared values that guide how we work, innovate, and support our customers.

About The Role

We're looking for a Lead Data Scientist to help build and advance IXOPAY's AI Payments Intelligence platform.

In this hands‑on technical leadership role, you'll design and develop machine learning and AI capabilities that transform complex payment data into actionable intelligence for global merchants.

Working closely with Engineering, Product, and customers, you'll build production‑ready models and AI‑driven solutions that help merchants improve payment performance, optimize costs, manage risk, and make smarter decisions using their payment data.

You'll own initiatives across the full data science lifecycle - from exploration and feature engineering through model development, deployment, and monitoring - while mentoring other data scientists and helping shape IXOPAY's broader AI and data science practices.

What You'll Do

• Build AI & Machine Learning Solutions
• Design, develop, and operate the machine learning and AI capabilities behind IXOPAY's AI Payments Intelligence platform.
• Build production‑ready models for anomaly detection, payment performance monitoring, transaction optimization, routing intelligence, forecasting, fraud and risk, and predictive analytics.
• Develop LLM-powered capabilities, including intelligent agents, automated decision systems, and real‑time or near‑real‑time inference workflows.
• Evaluate emerging AI and machine learning techniques and identify opportunities to apply them to meaningful customer and payment challenges.
• Own the Data Science Lifecycle
• Take hands‑on ownership from data exploration and feature engineering through model development, validation, deployment, monitoring, and continuous improvement.
• Work with large‑scale transaction data from PSPs, acquirers, gateways, and other payment systems, ensuring data quality and consistency across analytical workflows.
• Implement model monitoring, explainability, alerting, and drift detection to ensure AI capabilities remain reliable and trustworthy in production.
• Translate complex analytical findings into clear insights, metrics, dashboards, and recommendations that customers can use to improve payment performance.
• Build Scalable Data & AI Infrastructure
• Partner with Backend, Data, and Platform Engineering teams to design scalable data pipelines, schemas, feature stores, and model‑serving infrastructure.
• Contribute to architectural decisions and technology choices across IXOPAY's AI and data science ecosystem.
• Build cloud‑native machine learning solutions using AWS and modern data processing technologies.
• Establish engineering and MLOps practices that enable models to move reliably from experimentation into production.
• Lead and Collaborate
• Mentor and provide technical guidance to Data Scientists and Machine Learning Engineers, helping strengthen capabilities and best practices across the team.
• Partner with Product leadership to define requirements, evaluate new AI capabilities, and guide initiatives from concept through production.
• Collaborate with customer‑facing teams and enterprise customers to understand payment challenges and identify opportunities where data science can deliver measurable value.
• Balance independent technical ownership with collaborative delivery across Engineering, Product, and Data teams.
• What You'll Bring
• Required
• Extensive professional experience in Data Science, Machine Learning, Applied AI, or a related field.
• Advanced degree in Mathematics, Physics, Computer Science, Data Science, or a related quantitative discipline, or equivalent practical experience.
• Advanced Python and SQL skills with strong knowledge of data structures, algorithms, and statistical computing.
• Proven experience building, deploying, and owning production machine learning models end‑to‑end.
• Strong experience with forecasting, anomaly detection, predictive modeling, or tabular machine learning using technologies such as Light GBM, XGBoost, or Cat Boost.
• Strong understanding of probability, statistics, stochastic modeling, and time‑series forecasting.
• Hands‑on experience with AWS and cloud‑native data and AI architectures, including technologies such as S3, Lambda, Dynamo DB, SQS, Cognito, Bedrock, and boto3.
• Experience with modern data science and processing technologies such as Pandas, Num Py, Sci Py, Spark, Kubeflow, or Vertex AI.
• Experience with MLOps, CI/CD, Git, Docker, and containerized architectures.
• Experience mentoring Data Scientists or Machine Learning Engineers and providing technical leadership across complex initiatives.
• Strong communication skills with the ability to translate complex analytical concepts into clear business and customer outcomes.
• Professional fluency in English.
• Preferred
• Payments, Fin Tech, payment processing, acquiring, fraud, or risk management.
• Building forecasting or prediction models for payment performance and transaction‑level data.
• Analytical and OLAP technologies such as Click House, Snowflake, or Duck DB.
• Monitoring and visualization technologies such as Grafana and Streamlit.
• Building LLM‑powered applications, intelligent agents, or AI‑driven decision systems.
• Working with high‑volume transactional datasets and real‑time or near‑real‑time inference.
• Experience in a startup, scale‑up, or other fast‑moving technology environment.

Why Join IXOPAY?

At IXOPAY, you'll help build the intelligence layer behind the future of enterprise payments.

You'll work with large‑scale, real‑world payment data to develop AI and machine learning capabilities that help global merchants improve performance, reduce costs, manage risk, and make smarter payment decisions.

You’ll have significant technical ownership, influence the architecture and direction of our AI Payments Intelligence platform, and collaborate with experienced Engineering, Product, and payments teams in an international environment.

• We Offer
• Competitive salary and benefits
• Professional growth and technical leadership opportunities
• A collaborative, international engineering culture
• Flexible remote working with the option to work from our Munich office.
• Location

This is a remote-friendly position based in Germany.

We welcome applications from candidates across Germany or the European Union., with a preference for those located in or near Munich.

You'll have the flexibility to work remotely or from our Munich office.

What Makes an IXOPAYer?

We are a global team united by one standard, where every voice matters and initiative drives real change.

We believe in progress over perfection—moving with purpose, embracing modern technologies and AI, and continuously improving through learning and iteration.

We empower our people to take ownership, challenge the status quo, and collaborate across teams to solve meaningful problems.

If you're curious, customer‑focused, and passionate about shaping the future of global payments, you'll thrive at IXOPAY.

Our Commitment to Inclusion

We know great candidates don't always meet every qualification.

Equal Opportunity Employer

IXOPAY is committed to building an inclusive workplace where everyone can thrive.

We welcome applications from all qualified candidates regardless of race, ethnicity, religion, gender, gender identity or expression, sexual orientation, age, disability, or any other characteristic protected by applicable law.

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