Data Scientist
- Full-Time
- Minneapolis, MN
- Ameriprise Financial
- Posted 4 years ago – Accepting applications
Job Description
Support business decision-making by providing financial, statistical and predictive analytical solutions that leads to solutions for business issues.
Responsibilities
Required Qualifications
Preferred Qualifications
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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.