Morgan Stanley is seeking a Non-Financial Risk Data Scientist Analyst in Budapest to help develop advanced analytics and machine learning solutions for non-financial risk management. The ideal candidate will leverage data science skills to build innovative predictive models and contribute to strategic risk assessment initiatives.
As a Non-Financial Risk Data Scientist Analyst, your primary responsibilities will involve developing sophisticated data-driven solutions to identify, analyze, and mitigate non-financial risks across the organization. You will design and implement advanced machine learning algorithms, create predictive models, and generate actionable insights that support strategic decision-making processes.
The role requires strong technical expertise in data science, with significant experience in statistical analysis, machine learning techniques, and programming. Candidates must possess advanced skills in Python, R, or similar data science programming languages, demonstrating proficiency in data manipulation, model development, and statistical inference. A strong academic background in computer science, statistics, mathematics, or a related quantitative field is essential, along with proven experience in developing complex predictive models.
Morgan Stanley offers a competitive compensation package, professional development opportunities, and exposure to cutting-edge risk management technologies. The position provides a dynamic work environment where innovative data scientists can make meaningful contributions to global risk management strategies, with potential for career growth and advancement within a leading financial institution.
