About Our Company
We’re a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. Our team of 22,000 people across 19 countries, serves more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses – Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.
Job Description
Ameriprise Financial is looking to add a Data Scientist Manager to the team! This individual will play an integral role in supporting modeling, data analysis and database needs for the assigned line of business (Asset Management). You will manage the creation and/or usage of large data sets, provide information-based decision logic and predictive modeling solutions, and translate modeling and analytic output into understandable, actionable business knowledge, insight, and applications. You will demonstrate strong technical and problem-solving skills while supporting multiple projects collaboratively.
Key Responsibilities
- Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, and optimization solutions to support Asset Management business objectives.
- Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation.
- 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.
- Monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.
- Identify and execute targeting and optimization opportunities.
- Embed analytic programs and tools within business processes, ensuring 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.
- Provide technical guidance and informal leadership to analytic resources, including coaching on best practices for the usage and application of analytic output, as appropriate for a manager-level role.
Required Qualifications
- Master's degree or equivalent Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.)
- 3 - 5 years relevant analytics or data science experience.
- 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, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies.
- Experience with statistical programming (SAS, R, 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.
- Ability to work effectively in a collaborative team environment.
Preferred Qualifications
- Ph.D
- 3+ years of experience in statistical modeling and the collating processes necessary to create modeling data.
- Experience with big data technologies which may include Hadoop, Cloud Computing Environments (including container creation, management & deployment), Spark, Dataiku, Amazon SageMaker etc.
- Self-starter with the ability to work effectively in a matrix environment while (at times) working autonomously.
- Proven flexibility and adaptability in effectively driving results in an environment of changing priorities.
- Background in asset management or financia