Ameriprise Financial is looking to support modeling and data analysis, budget execution, and the FinOps needs of the business by leveraging advanced analytical solutions and predictive modeling techniques.
Requirements
- Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
- Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, machine learning, clustering, or similar methodologies.
- Experience with statistical programming (SAS, R, Python, SQL etc.) & data visualization software in a data-rich environment.
- Experience with cloud services and big data technologies FinOps.
- Background in financial services.
- 3+ years of experience in statistical modeling and the collating processes necessary to create modeling data.
- Experience with predictive modeling, advanced machine learning techniques, simulation, optimization solutions, and risk management purposes.
Responsibilities
- Identify, develop, and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, and risk management purposes.
- Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation.
- Identify and execute targeting and optimization opportunities while consulting and coordinating execution with asset owners.
- 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.
Other
- Master degree or equivalent Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.).
- 5-7 years relevant experience required.
- 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.
- Ability to work effectively in a collaborative team environment.
- Self-starter with the ability to work effectively in a matrix environment while (at times) working autonomously.
