Perform sophisticated analytics to provide actionable insights that improve business outcomes and minimize risk
Provide consultation to business leaders and other stakeholders on how to leverage analytics insights
Lead small projects with manageable risks and resource requirements
Act as a resource for teammates with less experience
Extract and evaluate information gathered from multiple sources, resolve data conflicts and provide recommendations to diverse audiences
Co-design optimal solutions to solve complex business problems with advanced data science capabilities

Bachelor’s degree in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
Minimum of six years of related experience
Demonstrate domain expertise (SME) in one or more areas relevant to banking, financial services, fin-tech, quantitative risk management, and/or financial regulation
In-depth knowledge in practices, theories and methodologies associated with the professional discipline such as statistics, programming (such as Python, R, SAS, etc.), machine learning, model development, business information visualization
Ability to maintain a high level of competency in statistical and analytical principles, tools, and techniques
Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
Experience in managing multiple projects with tight deadlines in a collaborative environment

Data Scientist III – Fraud Analytics

Key skills