Data Scientist Manager

Ameriprise Financial Services; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Ameriprise Financial is seeking a Data Scientist Manager to lead client analytics initiatives, deploying AI at scale and guiding production-ready solutions across the business. In this senior role you will partner with stakeholders, frame problems, deliver insights, mentor peers, and advance governance and best practices in AI, ML, and analytics within a collaborative, hybrid work environment.

The position emphasizes cross-team collaboration, scalable architectures, and staying current with AI

Qualifications

• Master's degree in quantitative discipline.
• 3-5 years of relevant experience delivering advanced analytics, machine learning, or applied AI.
• Strong foundation in statistics, predictive modeling, and machine learning.
• Experience with Python, SQL, and ML frameworks.
• Experience with cloud platforms, preferably AWS or Snowflake.
• Ability to independently own complex problems and deliver production-ready solutions.
• Ability to present technical materials to both technical and non-technical partners.

Responsibilities

• Design and implement AI and ML solutions addressing complex business problems across client and advisor analytics.
• Translate ambiguous business needs into analytical approaches with stakeholders; define success measures.
• Support the full lifecycle from problem framing to deployment and monitoring.
• Lead analytics strategy for the recommendation engine with product and technology teams.
• Ensure governance, validation, and monitoring standards for data, models, and AI solutions.
• Mentor peers, promote best practices, and stay current on AI and analytics trends.

Skills

Statistics

Predictive modeling

Machine learning

Python/SQL

Data visualization

Communication

Education

Master's degree in quantitative discipline

Tools

Python

SQL

ML frameworks

Job description

About Our Company

We're a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. Our team of 22,000 people across 19 countries, serves more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses - Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.

Job Description

Ameriprise Financial has an opportunity for a Data Scientist Manager to join the team supporting Client Analytics. This is a senior individual contributor role with technical and analysis leadership responsibilities. You will play an integral role in influencing client and advisor strategy and deploying AI at scale. This position operates as a technical leader and trusted partner to business teams, owning complex problems end to end from solution design through production deployment and translating these solutions into actionable insights and data-driven recommendations.

Key Responsibilities

• Design and implement AI and machine learning solutions that address complex, real-world business problems across client and advisor analytics, using statistical analysis, forecasting, predictive modeling, machine learning, and GenAI.
• Translate ambiguous business needs into clear analytical approaches by partnering with business stakeholders to frame problems, define success measures, develop hypotheses, and communicate actionable insights and recommendations.
• Support the full lifecycle of data science and AI solutions from problem framing, data exploration, and feature engineering through model development, validation, deployment, monitoring, and continuous improvement.
• Lead the analytics strategy and ongoing enhancement of the field-facing recommendation engine, partnering closely with product and technology teams to develop, maintain, monitor, and improve recommendation solutions that support personalization, prioritization, and business decision-making.
• Ensure solutions meet data, model, and AI governance standards by applying enterprise policies, responsible AI practices, validation expectations, documentation standards, and ongoing performance monitoring.
• Serve as a technical leader and thought partner by advancing data science best practices, identifying opportunities for scalable and automated solutions, mentoring peers through knowledge sharing, and staying current on emerging AI, machine learning, and analytics techniques.

Required Qualifications

• Master's degree in quantitative discipline (i.e., Data Science, Statistics, Computer Science, Mathematics, Economics or a related field).
• 3-5 years of relevant experience delivering advanced analytics, machine learning, or applied AI solutions.
• Strong foundation in statistics, predictive modeling, and machine learning.
• Proven experience with modern data science tools, data visualization tools, and programming languages (e.g., Python, SQL, ML frameworks).
• Experience working in cloud‑based platforms, preferably AWS or Snowflake.
• Proven ability to independently own complex problems and deliver production‑ready solutions.
• 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 and support multiple projects at one time.

Preferred Qualifications

• Experience building solutions using LLMs, Agentic AI, RAG, and more traditional AI techniques.
• Familiarity with MLOps practices, CI/CD for models, and production monitoring.
• Experience using large-scale data sets.
• Familiarity with financial advisor, client, or customer analytics
• Experience working in financial services or other highly regulated industries.

In-Office Collaboration

We are a client-centric, relationship-based business. Working together, in-person, is foundational to how we achieve results. By fostering a culture of face-to-face collaboration, idea sharing, productivity and personal connection, we deliver for our stakeholders - clients, advisors, employees and shareholders. Our employees work in the office at least four (4) days per week, with flexibility to work from home one (1) day per week. Some roles may require additional in-office time or different in-office expectations, and specific requirements will be discussed during the hiring process.

Visa Sponsorship

Applicants must have a valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States (e.g., H-1B, F-1 CPT, F-1 OPT, TN).

Base Pay Salary

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