Senior AI & Analytics Leader, Operations

Ameriprise Financial Services, LLC

Minneapolis (MN)

Hybrid

USD 131,000 - 180,000

Full time

29 hours ago
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Job summary

Ameriprise Financial Services, LLC is seeking a Senior Data Scientist Manager to join the Operations Analytics team. This role leads technical efforts, designs AI at scale, and translates complex problems into actionable data-driven insights for decision-makers.

The position emphasizes end-to-end ownership from problem framing to deployment, governance, and ongoing optimization, with collaboration across product and technology to enhance recommendations and impact business outcomes.

Qualifications

  • Master’s degree in quantitative discipline (e.g., Data Science, Statistics, CS, Economics).
  • 5–7 years of experience delivering advanced analytics, ML, or AI solutions.
  • Strong foundation in statistics, predictive modeling, and ML.
  • Experience with Python, SQL, ML frameworks.
  • Experience on cloud platforms, preferably AWS or Snowflake.
  • Ability to own complex problems and deliver production-ready solutions.
  • Strong communication to non-technical partners.

Responsibilities

  • Design and deploy AI/ML solutions across Service and Operations analytics.
  • Translate business needs into analytical approaches with stakeholders.
  • Own problem framing, data exploration, modeling, deployment, and monitoring.
  • Lead enhancements of the field-facing recommendation engine with product/tech teams.
  • Ensure governance, documentation, and ongoing monitoring of models.
  • Mentor peers and stay current with AI/ML techniques.
  • Deliver analytics strategy with measurable business impact.

Skills

Data science
Statistics
Predictive modeling
Machine learning
Python
SQL
ML frameworks
Cloud platforms

Education

Master’s degree

Tools

AWS
Snowflake

Job description

Ameriprise Financial Services, LLC is seeking a Senior Data Scientist Manager to join the Operations Analytics team. This role leads technical efforts, designs AI at scale, and translates complex problems into actionable data-driven insights for decision-makers.

The position emphasizes end-to-end ownership from problem framing to deployment, governance, and ongoing optimization, with collaboration across product and technology to enhance recommendations and impact business outcomes.

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