Director Data Scientist

Ameriprise Financial Services, LLC•Minneapolis, MN

15d•$150,000 - $206,300•Hybrid

About The Position

The Director of Client Analytics is a people and analytic leadership role responsible for advancing client strategy through scalable data science, AI, and advanced analytics solutions. This role leads a team of data scientists and partners with senior business leaders to translate complex data, predictive models, and analytic insights into clear business recommendations that improve client outcomes and inform strategic decisions. This is a fast-paced role focused on highly visible, high-impact analytics initiatives that directly support business execution and senior leadership priorities.

Requirements

Master’s degree in quantitative discipline (i.e., Data Science, Statistics, Computer Science, Mathematics, Economics or a related field).
7-10 years of experience in analytic or data science role
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.
Strong knowledge of advanced statistical, machine learning, and optimization techniques, with the ability to apply the right method to the business problem
Experience with statistical programming (Python, SQL, etc.) & data visualization software in a data-rich environment.
Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.
Ability to work effectively and influence in a collaborative team environment
Ability to manage multiple projects at one time, delegate and prioritize work
Proven experience with MLOps practices, CI/CD for models, and production monitoring.

Nice To Haves

Experience building solutions using LLMs, Agentic AI, RAG, and more traditional AI techniques.
People leadership experience
Experience and knowledge of Ameriprise field structure and hierarchy
Advisor, client, and industry knowledge
Experience working in financial services or other highly regulated industries.

Responsibilities

Engage collaboratively with business leaders and analysts to provide analytical thought leadership. Identify and interpret business needs, define high-level requirements, strategy, scope, and technical risks, and align analytics and AI capabilities to top business priorities.
Deliver analytic strategy that delivers measurable business impact.
Develop, document, and communicate business-driven analytic solutions, translating advanced modeling, segmentation, predictive analytics, and advisor and client intelligence into clear, actionable insights that influence decision-making and execution.
Identify, develop, and implement complex analytical solutions leveraging predictive modeling, advanced machine learning techniques, optimization, simulation, experimentation, and personalization.
Contribute to ongoing expansion of data science expertise and credentials by keeping up with industry best practices, developing new skills, and knowledge sharing. Work cross functionally to develop standardized/automated solutions and adopt best practices.
Set technical direction for complex analytical solutions, including predictive modeling, machine learning, optimization, simulation, experimentation, and personalization, with a focus on scalable and business-ready delivery.
Build, lead, and scale a high-performing analytics team, fostering a culture of curiosity, innovation, accountability, and continuous learning. Provide coaching, performance management, hiring, development, and goal setting for team of data scientists.
Manage data and dataset creation, including data extraction, feature engineering, data quality controls, and validation processes. Monitor the execution and performance of analytical solutions from criteria definition through delivery and results capture.
Ensure adherence to enterprise and industry data, model, and AI governance standards. Partner with governance leaders to manage risk, compliance, and ethical use of analytics and AI capabilities across the team.