Data Science Senior Manager, Financial Crimes
**Note: Only US Citizen or GC Holder Eligible
Need 6 Years
Job Title: Data Science Senior Manager, Financial Crimes

Location: Brooklyn, OH, US
Work Type: Onsite | Remote | Hybrid
Employment Type: Permanent
Additional Compensation: Base plus bonus
Sponsorship: Not available
Relocation: Not available
Reports To: Senior Leadership
Direct Reports: None
Work Hours: Not flexible

Job Description

About the Role

The Data Science Senior Manager in Financial Crimes leads a team dedicated to quantitative analysis, including model development, validation, and maintenance. This role is pivotal in setting team priorities, assigning tasks to appropriate resources, and harnessing team strengths to surpass performance expectations. This individual will guide modeling practices and data strategies, utilizing current and emerging technologies to meet organizational goals. Acting as a strategic advisor, the Senior Manager will engage with senior leadership to drive impactful outcomes across the business.

Key Responsibilities
Strategic Consultation & Leadership

Offer thought leadership and strategic insights to senior/executive business partners.
Drive team output, ensuring executive-ready deliverables aligned with business priorities.
Identify industry trends, anticipate needs, and influence data sourcing strategy.
Team Development

Proactively mentor and develop team members in technical skills.
Promote the team's capabilities and build influence within the organization.
Guide and coach team on building complex data models and establishing best practices.
Collaboration & Partnership

Partner across levels and departments, guiding and challenging to drive impact.
Develop holistic strategies and solutions aligned with LOB priorities, taking cross-functional dependencies into account.
Model Building & Maintenance

Set standards for modeling practices, forecast future tools/techniques, and leverage emerging industry methods.
Communicate technical insights effectively to both technical and non-technical audiences.
Required Qualifications

Education:

Master's degree in a quantitative field (e.g., statistics, mathematics, economics, data science) and 6+ years of experience; or
Bachelor's degree in a quantitative field and 7+ years of experience.

Technical Skills:

Proficiency in advanced Microsoft Office, SQL/NoSQL, Python/R/SAS, and distributed computing.
Knowledge of data structure relationships, ETL, and unstructured data handling.
Expertise in cloud-based computing environments.

Data Literacy:

Strategic perspective on data sourcing, including emerging industry trends and technologies.
Ability to lead high-level discussions on applications with senior leadership.

Competencies:

Leadership: Manage and integrate team activities; promote team capabilities.
Partnering & Influencing: Strategic advisor to senior leadership, guiding and influencing outcomes.
Business Acumen: Cross-functional understanding of the business and industry best practices.
Critical Thinking: Systematic, forward-looking problem solver with the ability to "connect the dots."
Communication: Strong written/verbal skills; adept at simplifying complex concepts and presenting to senior audiences.

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