Changing the world through digital experiences is what Adobe’s all about. We give everyone from emerging artists to global brands everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.
We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
The Sr. Fraud Data Analyst uses their technical skills to identify fraud trends, automate processes, provide data driven insights, draw conclusions and recommendations.
The candidate has a passion for fraud detection and creativity providing solutions towards wide variety of business problems using data.
The analyst will work with different partners across Adobe to develop best in class fraud detection capabilities.
What you'll Do
Exceptional analytical ability and good eye for business with at least 10 years of relevant experience.
Collaborate with multi-functional data teams to develop scalable and reusable frameworks for evaluating large datasets on the most pressing business questions
Perform data analyses to gain insights and detect fraud and abuse across platforms and products.
Automate manual workflows to build efficiencies across investigations and operational workflows.
Improve tools through data analysis, technical expertise, and presentations to key partners.
Translate investigations and intel into root cause analysis to find opportunities for scale.
What you need to succeed
Master's Degree or Bachelor's Degree along with relevant experience preferably in mathematics, information systems, data analysis.
8+ years of data analytics experience.
2+ years of fraud analytics experience.
Deep Technical proficiency in SQL.
Substantial experience with data visualization platforms (e.g. Power BI, Tableau, Looker).
Ability to calculate fraud, risk and abuse trends.
Experience in business and fraud analytics and insights.
Ability to identify the root cause of problems and identify, propose, and recommend innovative solutions.
Ability to work in terminal environments.
Exposure to ML / AI or tools such as R, Python is nice to have.
Experience using statistics (A / B testing, regression, etc) is a plus.