Senior Data Scientist

Role overview This role places a senior data scientist on the front line of financial crime prevention, embedded within a Customer Success organization that partners directly with banks, payment networks, and acquirers. The work blends hands-on model development with client-facing consulting, helping institutions deploy and tune fraud and risk detection solutions that safeguard large volumes of payment traffic. The team works cross-functionally with Research, Product, and Engineering to refine processes, tooling, and best practices.

Responsibilities - Understand, clean, and validate client-provided datasets before they are used in modeling - Preprocess data using shell scripts alongside a programming language such as Python, Java, or Scala - Iteratively compute features and tune parameters to improve model quality and stability - Communicate findings to project managers and help shape data science decisions on each engagement - Collaborate with client stakeholders including data scientists, engineers, and risk managers - Partner with internal Product and Research teams to improve processes, best practices, and tooling

Requirements - MSc or PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, or a related field - Proficiency in machine learning fundamentals, including training, testing, and avoiding overfit - Experience with big data technologies such as Spark and Hadoop - Strong skills in bash and Python, plus working proficiency in Java or Scala - Knowledge of resource monitoring and runtime optimization at both JVM and operating system level - Clear oral, presentation, and written communication skills for client-facing work

Nice to have - Fraud or digital business domain experience - Customer-facing consulting experience - Knowledge of statistics or data visualization - Familiarity with tree-based algorithms such as Random Forests, XGBoost, or LightGBM