Manager, Fraud Analytics
Role Overview
Uses advanced analytics and technologies, including machine learning, deep learning, and artificial intelligence, to analyze structured and unstructured data.
Develops data modeling processes and predictive models that support business decisions, customer experience, and productivity.
Collaborates with data and analytics teams to refine and scale analytics into mature solutions.
The role may focus on a business group or have broader enterprise-wide scope.
Key Skills for This Role
Full Job Posting
Role overview
Uses advanced analytics and technologies, including machine learning, deep learning, and artificial intelligence, to analyze structured and unstructured data.
Develops data modeling processes and predictive models that support business decisions, customer experience, and productivity.
Collaborates with data and analytics teams to refine and scale analytics into mature solutions.
The role may focus on a business group or have broader enterprise-wide scope.
Responsibilities
- Develop data strategies and mine data to assess the feasibility of AI and machine learning solutions.
- Analyze large datasets to identify patterns and trends and provide recommendations to business leaders.
- Develop predictive systems and machine learning algorithms; investigate tools for innovative business data solutions.
- Work with product teams and partners on data-driven decisions, business planning, and future roadmaps.
- Provide specialized consulting, analytical, and technical support; handle non-routine problems independently.
- Apply the Risk Management Framework and relevant policies, standards, procedures, laws, and regulations in decision-making.
Qualifications
- Intermediate proficiency in mathematics, statistics and operations research, deep learning, machine learning, trust, bias and ethics, creative thinking, and critical thinking.
- Advanced proficiency in big data, data visualization, computational thinking and programming, data wrangling, and data preprocessing.
- Advanced verbal and written communication, collaboration, analytical and problem-solving, influence, and data-driven decision-making skills.
- Typically 5–7 years of relevant experience and a related post-secondary degree or equivalent education and experience.
- Deep knowledge and technical proficiency gained through extensive education and business experience.
Nice to have
- Experience in fraud analytics or detection, experience with FICO/FIQM, and knowledge of Java are nice to have.
Compensation
- The stated salary range is $80,000–$175,000; the posting identifies the pay type as salaried.
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