Remote - Lead BSA Data Scientist

We’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.

JOB DESCRIPTION

Job Summary:

The Lead BSA Data Scientist plays a critical role in leveraging data analytics to enhance Bank Secrecy Act (BSA) compliance and Anti-Money Laundering (AML) efforts. This role involves developing advanced models, algorithms, and analytics solutions to detect suspicious activities, mitigate financial crime risks, and ensure regulatory adherence. The Senior BSA Data Scientist collaborates with compliance, risk management, and technology teams to drive data-driven decision-making and improve fraud detection capabilities.

Key Responsibilities:

• Develop and implement machine learning models to identify potential money laundering and fraud risks.

• Analyze large datasets to detect patterns, anomalies, and trends related to financial crime.

• Enhance transaction monitoring systems using predictive analytics and AI-driven solutions.

• Collaborate with compliance teams to refine BSA/AML risk assessment methodologies.

• Conduct statistical analysis to improve the effectiveness of suspicious activity reporting (SAR).

• Work with engineering teams to integrate data science solutions into compliance platforms.

• Provide insights and recommendations to senior leadership based on data-driven findings.

• Stay updated on regulatory changes and emerging financial crime trends to refine models accordingly.

Compliance Requirement:

All employees in this role are required to complete and maintain current training in Bank Secrecy Act (BSA), Anti-Money Laundering (AML), and Office of Foreign Assets Control (OFAC) regulations. This includes initial onboarding training and ongoing annual refreshers, as mandated by Green Dot’s compliance policies. Non-compliance could pose reputational, legal, and financial risks to the organization.

Qualifications:

• Bachelor’s degree in data science, Computer Science, Statistics, Finance, or a related field.

• 5 years of experience in data science, analytics, or financial crime prevention.

• Strong knowledge of BSA, AML, KYC , and financial regulations.

• Expertise in Python, R, SQL, and machine learning frameworks.

• Experience with big data technologies such as Hadoop, Spark, or cloud-based analytics platforms.

• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications:

• Master’s degree in a relevant field.

• Certification in Certified Anti-Money Laundering Specialist (CAMS) or Certified Fraud Examiner (CFE) .

• Experience working with regulatory agencies or financial institutions.

POSITION TYPE

Regular

PAY RANGE

The targeted full-time base salary for this position is $120,700 to $180,900 per year. The final compensation will be determined by a number of factors such as qualifications, expertise, and the candidate’s geographical location.

We’re Here to Support You—Accommodations Upon Request

Green Dot is committed to providing an inclusive and accessible hiring experience for all candidates. If you require a reasonable accommodation during any part of the application or interview process, we encourage you to let us know. We will work with you to meet your needs in a way that respects your privacy and ensures equal opportunity. Our goal is to support every applicant in showcasing their talents and potential.

Work Authorization Requirement

At Green Dot Corporation, we value diversity and strive for fair and inclusive hiring practices. However, we are currently unable to offer visa sponsorship. All applicants must be legally authorized to work in the United States at the time of application and throughout the duration of employment, without the need for current or future sponsorship.

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