Senior Data Scientist (Model Risk Office)

Quick Facts

• Role: Senior Data Scientist (Model Risk Office)

• Focus: Model risk assessment and guidance for reliable, production-grade algorithms

Description

You will be part of the Model Risk Office, analyzing data science implementations for methodology and assumption gaps and identifying risks in algorithms under development. You will work across multiple approaches—including ML, optimization/OR, deep learning, and GenAI—and partner with global teams to close identified gaps. The work emphasizes reliability, resilience, and production-quality execution.

Responsibilities

• Partner with product teams and business leaders to understand problems and ensure reliable algorithmic solutions with data science/AI/data engineering teams

• Develop insights that guide other data scientists to create positive business and people impact

• Work with large-scale systems and pipelines using big datasets

• Apply machine learning techniques and algorithms to answer business questions and propose solutions

• Further develop expertise in machine learning, statistics, optimization, GenAI, and advanced analytical models

• Review and write production-grade code using best practices

• Help improve the understanding of building and maintaining resilient algorithmic pipelines

Requirements

• Master’s in a quantitative degree (or Bachelor’s/Engineer with sufficient consecutive data science experience)

• At least 5 years of Data Science experience, including at least 3 years with production-grade data science/algorithmically enabled applications

• Strong coding ability; Python and Spark are preferred

• Strong technical and analytical skills (machine learning, optimization/OR, simulation, predictive modeling, etc.)

• Proven leadership, problem-solving, and prioritization experience

• Strong attention to detail, curiosity, and collaboration; comfortable working across teams

Benefits

• International Data Science team with global responsibilities

• Long-term career development and growth opportunities

• Competitive salary and benefits (private health care, life insurance, stock options, saving plans, lunch subsidy, sports cards, in-office fitness center)

• Trainings, certifications, conference participation, and internal coaching programs

• Flexible working arrangements in a hybrid model