Ameriprise Financial has an exciting opportunity for a Senior Manager of Predictive Analytics to join the team! This role will provide the opportunity to leverage sophisticated analytics to profile key characteristics of successful advisors. The individual in this position will play an integral role in leading projects from design through implementation and monitoring; building financial based models and tools for complex analysis across the advisor population to help accomplish goals and objectives. Key Responsibilities Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, simulation, optimization solutions, etc. Ensure continued accuracy, relevancy, and effectiveness and track process improvements once deployed. Curate and structure data for optimal use in analytics as it relates to advisor risk metrics. Provide insights into quality, and completeness of data and other standard risk metrics to facilitate. Under direction of the Sr. Leader, collaborate with business leaders and/or analysts to provide analytical thought leadership and support for business problems. Identify and interpret business needs, define high-level business requirements, strategy, technical risks, and scope. Develop, document, and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge leading to solutions for advisor performance and risk, making recommendations for action as appropriate. Provide direct and/or indirect leadership and lower-level analysts including; coaching, development and sharing of expertise to drive team results. Ensure adherence to data and model governance standards that are set and enforced by industry standards and/or enterprise and business unit data governance polices and leaders. Required Qualifications 5-7 years of experience in a finance or quantitative risk role Master's degree or equivalent with focus in finance, math, statistics, economics or quantitative field Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, clustering, or similar methodologies. Experience with statistical programming (R, Python, SQL etc.) & data visualization software. Proven ability to present/communicate complex, technical materials in a way that facilitates decision making and drives outcomes; ability to communicate to less technical partners. Ability to work effectively in a collaborative team environment. Preferred Qualifications In-depth knowledge of financial services industry with a focus in risk and ability to articulate key concepts to others. Strong relationship and communication skills in influencing across multiple business areas on recommendations and analysis results and the ability to clearly articulate complex analytical concepts. Experience working in an AWS environment.