Senior Associate, Data Scientist - Operational Risk Management

Experteer Overview In this role you will be a data science builder focused on operational risk analytics at scale. You will work with a cross-functional team to turn data into strategic risk insights that inform governance and decision-making. You will experiment with cutting-edge ML techniques and NLP/Generative AI to deliver next-generation risk features. The role combines technical execution with clear storytelling to drive business impact and risk management improvements. Compensation / Benefits * Collaborate with data scientists, software engineers, and product managers to deliver a product customers love * Leverage a broad tech stack (Python, Conda, AWS, H2O, Spark, and more) to extract insights from large numeric and textual datasets * Build machine learning models through all development phases: design, training, evaluation, validation, and deployment * Translate complex technical work into tangible business goals through strong communication Tasks * Bachelor in a quantitative field with 2+ years of data analytics experience or Master in a quantitative field or MBA with quantitative concentration * Experience with AWS * At least 2 years of experience with Python, Scala, or R * At least 2 years of experience with machine learning * Experience with SQL * Experience with clustering, classification, sentiment analysis, time series, and deep learning * Ability to retrieve, combine, and analyze data from diverse sources and structures * Familiarity with evaluating models (confusion matrix, ROC) and backtesting Key requirements * Health benefits * Competitive salary by location * Performance-based incentive compensation * Inclusive, supportive culture * Career growth opportunities * Sponsorship available for qualified applicants

Risk field with 2+ years of data analytics experience or Master in a quantitative field or MBA with quantitative concentration, * Experience with AWS * At least 2 years of experience with Python, Scala, or R * At least 2 years of experience with machine learning * Experience with SQL * Experience with clustering, classification, sentiment analysis, time series, and deep learning * Ability to retrieve, combine, and analyze data from diverse sources and structures * Familiarity with evaluating models (confusion matrix, ROC) and backtesting Key requirements * Health benefits * Competitive salary by location * Performance-based incentive compensation * Inclusive, supportive culture * Career growth opportunities * Sponsorship available for qualified applicants