Senior Data Scientist Manager

DataJobs; Minneapolis (MN); Hybrid; USD 131,000 - 180,000; Full time

Benefits offered by this job

Vacation time

Sick time

401(k)

Health insurance

Life insurance

Variable pay

Job summary

Ameriprise Financial in Minneapolis, MN is seeking a Senior Data Scientist Manager to lead end-to-end AI and machine learning initiatives across Service and Operations analytics. The role combines technical ownership with stakeholder collaboration to deliver production-ready solutions and measurable business impact.

You will design and implement AI/ML solutions, translate business needs, own the full data science lifecycle, mentor peers, and advance governance and best practices in a fast-moving

Qualifications

• Master’s degree in a quantitative discipline (Data Science, Statistics, Computer Science, Mathematics, Economics, or a related field).
• 5–7 years of relevant experience delivering advanced analytics, machine learning, or applied AI solutions.
• Strong foundation in statistics, predictive modeling, and machine learning.
• Experience with modern data science tools, data visualization tools, and programming languages (e.g., Python, SQL, and 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 communicate complex technical material in a way that supports decision making, including communication to less technical partners.
• Ability to work effectively in a collaborative environment and support multiple projects at one time.

Responsibilities

• Design and implement AI and machine learning solutions that address complex business problems across Service and Operation analytics.
• Partner with business stakeholders to translate needs into analytical approaches, including problem framing and insights delivery.
• Own the full lifecycle of data science and AI solutions from data exploration to deployment and monitoring.
• Lead analytics strategy for a field-facing recommendation engine and collaborate with product and technology teams.
• Apply data, model, and AI governance standards with responsible AI practices and documentation.
• Act as technical leader by advancing data science best practices and mentoring peers.
• Deliver analytic strategy that results in measurable business impact.

Skills

Machine learning

Statistics

Predictive modeling

Data visualization

Python

SQL

ML frameworks

AWS

Snowflake

LLMs

Agents

RAG

CI/CD

GenAI

Education

Master’s degree in quantitative field

Tools

Python

SQL

ML frameworks

AWS

Snowflake

LLMs

Agents

RAG

CI/CD

GenAI

Job description

Ameriprise Financial is hiring a Senior Data Scientist Manager in Minneapolis, MN (hybrid) to lead end-to-end development of advanced AI and machine learning solutions across Service and Operation analytics. This role combines technical ownership with stakeholder partnership to turn complex problems into measurable, production-ready outcomes.

Responsibilities

• Design and implement AI and machine learning solutions that address complex, real-world business problems across Service and Operation analytics, using statistical analysis, forecasting, predictive modeling, machine learning, and GenAI.
• Partner with business stakeholders to translate ambiguous needs into clear analytical approaches, including problem framing, success measure definition, hypothesis development, and communication of actionable insights and recommendations.
• Own the full lifecycle of data science and AI solutions, from problem framing and data exploration through feature engineering, model development, validation, deployment, monitoring, and continuous improvement.
• Lead analytics strategy for ongoing enhancement of a field-facing recommendation engine, working with product and technology teams to develop, maintain, monitor, and improve recommendation solutions that support personalization, prioritization, and business decision-making.
• Apply data, model, and AI governance standards using enterprise policies, responsible AI practices, validation expectations, documentation standards, and performance monitoring.
• Act as a technical leader and thought partner by advancing data science best practices, identifying scalable and automated solution opportunities, mentoring peers through knowledge sharing, and staying current on emerging AI, machine learning, and analytics techniques.
• Deliver analytic strategy that results in measurable business impact.

Requirements

• Master’s degree in a quantitative discipline (Data Science, Statistics, Computer Science, Mathematics, Economics, or a related field).
• 5–7 years of relevant experience delivering advanced analytics, machine learning, or applied AI solutions.
• Strong foundation in statistics, predictive modeling, and machine learning.
• Experience with modern data science tools, data visualization tools, and programming languages (e.g., Python, SQL, and 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 communicate complex technical material in a way that supports decision making, including communication to less technical partners.
• Ability to work effectively in a collaborative environment and support multiple projects at one time.

Technologies

Python, SQL, ML frameworks, AWS, Snowflake, LLMs, Agents, RAG, CI/CD, GenAI

Preferred Qualifications

• Experience building solutions using LLMs, Agents, 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 operations analytics and call analytics.
• Experience working in financial services or other highly regulated industries.

Compensation

• Estimated base salary: $131,000–$180,100 per year.
• Pay-for-performance compensation philosophy.
• Initial total compensation may vary based on job-related knowledge, skills, experience, and geographical work location.
• Most roles are eligible for variable pay in the form of bonus, commissions, and/or long-term incentives depending on the role.

Benefits

• Vacation time
• Sick time
• 401(k)
• Health, dental and life insurances
• Variable pay in the form of bonus, commissions, and/or long-term incentives (depending on the role)

Work Arrangement

• 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, which will be discussed during the hiring process.

Visa Sponsorship

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

Additional Job Details

• Full time
• Exempt
• Job family group: Data
• Line of business: CSIRM Information Management