Address
Form of work
SalaryWe’re looking for talented professionals, anywhere in the United States, to join us in bringing smart money management and payment solutions to everyone’s fingertips.
At Green Dot, we are evolving to a new and permanent “Work from Anywhere” model designed to maximize the benefits of remote work, promote and enable a strong culture of performance and connectedness, and attract the best and brightest talent who align with our entrepreneurial spirit and mission.
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JOB DESCRIPTION
What does a Fraud Data Scientist do?
You will be responsible for using data to detect fraud and reduce fraud losses across the organization by data mining, testing, analyzing and transforming data into actionable insights. You will leverage statistical analysis to design and integrate models that support or automate decision making throughout the business.
As a Fraud Data Scientist, you can look forward to:
- Supporting Fraud prevention to utilize data to analyze, design, modify, document, and implement rules to address both fraud threats and unusual and suspicious activity
- Proactively analyzing all available data to identify emerging fraud trends
- Designing, developing and programming methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.
- Interacting with product and service teams to identify questions and issues for data analysis and experiments.
- Developing and coding software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
- Identifying meaningful insights from large data and metadata sources; interpreting and effectively communicating insights and findings from analysis and experiments to product, service, and business managers.
- Implementing models with technology and data engineers on various platforms.
- Using data visualization programs, tools and techniques to generate dashboards, reports and presentations that aid in data storytelling, understanding and interpretation of trends and patterns of business importance.
You might be the right match for this role if:
You are a self-starter who is able to deliver high quality work within tight deadlines. You have a passion for data and supplying customers with valuable insights. You are able to write excellent SQL and love working with analytic tools, using technical skills and creative approaches to solve unique problems. You also have the ability to learn the overall business and financial operations to provide relevant metrics and recommendations. You can lead and work with cross-functional teams
Ready to join us in our mission? These are the qualifications we are looking for:
Required:
- Minimum 10 years of data science or data analysis experience
- Bachelor’s Degree
- Strong expertise in programming languages such as SQL, SAS, Python, etc.
- Strong experience with concepts of customer segmentation, root cause/variance analysis, and extrapolation.
Preferred:
- Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering or related field
- Fraud industry experience
- Experience in a fraud rule / strategy role
- Experience with Falcon, PRM, VRM, Mastercard Connect and/or other rule platforms
- Experience with SageMaker or SAS
POSITION TYPE
Regular PAY RANGE
The targeted base salary for this position is $106,600 to $162,800 per year. The final compensation will be determined by a number of factors such as qualifications, expertise, and the candidate’s geographical location.<<>><<>><<>><<>><<>><<>><<>><<>><<>><<>>
Green Dot promotes diversity and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Green Dot provides reasonable accommodations for candidates on request and respects applicants' privacy rights.
