Data Scientist Manager

$118,200 - $159,600/Yr

Ameriprise Financial - Charlotte, NC

Part-time,Full-time - Mid Level

Charlotte, NC

10,001+ employees

Credit Intermediation and Related Activities

About the position

The Data Scientist Manager at Ameriprise Financial will lead efforts in modeling and data analysis to support marketing and digital analytics. This role involves managing large datasets, developing predictive modeling solutions, and translating analytical outputs into actionable business insights. The manager will oversee the end-to-end analytic solutions from ideation to implementation, ensuring adherence to data governance standards and contributing to the expansion of data science expertise within the organization.

Responsibilities

• Identify, develop and implement complex analytical solutions leveraging predictive modeling and advanced machine learning techniques for marketing and risk management.
• Manage dataset creation including data extraction, derived variable creation, and data quality control processes.
• Monitor execution of analytical solutions, including criteria specification, data sourcing, and back-end data capture results.
• Consult and coordinate campaign execution for direct to client campaigns.
• Identify and execute targeting and optimization opportunities.
• Collaborate with business leaders to provide analytical thought leadership and support for business problems.
• Define high-level business requirements, strategy, technical risks, and scope.
• Develop, document, and communicate business-driven analytic solutions and capabilities.
• Ensure continued accuracy, relevancy, and effectiveness of analytic programs and tools.
• Contribute to ongoing expansion of data science expertise by keeping up with industry best practices.

Requirements

• Master's degree or equivalent in a Quantitative Discipline (Finance, Statistics, Computer Science, etc.).
• 3 - 5 years of relevant experience in analytics.
• Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
• Experience with advanced statistical methods such as regression models, machine learning, and clustering.
• Proficiency in statistical programming (SAS, R, Python, SQL) and data visualization software.
• Ability to present complex technical materials to facilitate decision making.

Nice-to-haves

• Ph.D. in a relevant field.
• 3+ years of experience in statistical modeling.
• Experience with big data technologies such as Hadoop and Spark.
• Background in financial services.

Benefits

• Competitive salary and variable pay in the form of bonuses and commissions.
• Comprehensive benefits program supporting health and well-being.