Data Scientist Details

Ameriprise Financial - Minneapolis, MN

Employment Type : Full-Time

Support business decision-making by providing financial, statistical and predictive analytical solutions that leads to solutions for business issues.

Responsibilities

  • Identify, develop and implement complex analytical solutions leveraging predictive modeling techniques (ML and AI).
  • Develop, document, and communicate business-driven analytical solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.
  • 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.
  • 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.
  • Discuss complex industry-specific business concepts with executives, line managers and data scientists.
  • Conduct workshop sessions to identify AI/ML opportunities with business partner across Ameriprise Financials.

Required Qualifications

  • Bachelor degree in a highly quantitative field (Computer Science, Data Science, Statistics, Mathematics, etc.).
  • 4+ years of experience in developing AI & Machine learning models
  • Experience in leading executive briefings focused on AI / ML strategy, use case and roadmap development.
  • Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
  • Experience with statistical programming (SAS, 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.
  • Familiarity with AWS AI services (e.g., Amazon Personalize), ML platforms (Amazon SageMaker).

Preferred Qualifications

  • Masters or PhD in a highly quantitative field (Computer Science, Data Science, Operational Research, Statistics, Mathematics, etc.).
  • Strong organizational skills with an ability to manage numerous demands from internal / external stakeholders.
  • Ability to collaborate with multiple teams to drive adoption of AI/ML Solutions.

Posted on : 4 years ago