Job Description

Deploy models to draw meaningful insights about behavior, to inform decision-making and forecast into the future. This includes data collection & analysis, building and implementing models, and performance tracking. Implementing solutions is critical for success. Support business decision-making by providing financial or statistical analyses that lead to solutions for business issues, making recommendations for action as appropriate. Support projects from design through implementation and monitoring. Be the liaison between business leaders, staff, utility functions, and at times external parties to ensure information exchange and accomplish business objectives. Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, neural network etc.
Manage dataset creation including data extraction, data quality check, model development, and validation. May monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.
Under direction of the Sr. Leader, collaborate with business leaders and/or analysts to provide analytical thought leadership and support for business problems. Identify and interpret business needs, define high-level business requirements, strategy, technical risks, and scope.
Develop, document, and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.
Embed analytic programs and tools. Ensure continued accuracy, relevancy, and effectiveness and track process improvements once deployed.
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.
Capture and operationalize best-practice knowledge to drive machine learning more holistically (e.g., deploying a customer center of excellence).
Build deep relationships with senior individuals across Ameriprise to enable them to be AI/ML advocates.
Masters in Analytics, Machine Learning or a STEM field.
6+ years of experience in developing full-stack AI & Machine learning model & tools.
Experience in leading executive briefings focused on AI / ML strategy, use case and roadmap development.
Experience in data exploration and analytics to discover hidden patterns and insights.
Experience supporting accounting applications within the Financial Services industry (i.e. broker-dealer, asset management, banking, etc.) a plus.
Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
Experience conducting hands-on analytics projects using advanced statistical methods such as neural networks, or machine learning methodologies.
Experience with statistical programming (SAS, Python, SQL etc.) & data visualization software in a data-rich environment.
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.
Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.
Present results of analysis and/or recommendations to business partners. Communicate action plans and priorities to appropriate partners.
Demonstrable experience in building & deploying machine learning models.
Advanced AI & Machine learning techniques: Deep Learning (CNN, LSTM, etc.).
Machine Learning frameworks/environments: Tensor Flow, Keras, Scikit Learn, Torch etc.
Familiarity with AWS AI services (e.g., Amazon Personalize), ML platforms (Amazon SageMaker).
Ability to communicate complex topics to an audience with various functional knowledge, i.e. presentation skills with a high degree of comfort with both large and small audiences; High level of comfort communicating effectively across internal and external organizations. Masters degree or PhD in a highly quantitative field (Computer Science, Machine Learning, 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.
Experience and passion for designing and developing innovative AI/ML solutions that leverage natural language processing, computer vision, statistical learning theory.
Ability to think strategically about business, product, and technical problems and develop strategic, baselined, data modeling processes; ability to accurately identify cause-and-effect relationships.