Senior Data Scientist
$78.7k - $138.2kAmeriprise Financial Services, Inc.
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 Senior Data Scientist to the team! The individual in this role will support modeling, data analysis, and database needs for the assigned line of business (Columbia Threadneedle Investments Asset Management). You will create large data sets, provide information-based decision logic and predictive modeling solutions, and translate modeling/analytic output into understandable/actionable business knowledge, insight and applications. You will demonstrate strong technical and problem-solving skills and support multiple projects. Key Responsibilities
- Develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions to support Asset Management business objectives. May lead efforts on small-medium sized projects.
- Perform dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation.
- Monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results. Partner closely with leader and others to ensure proper delivery.
- Under direction of the Sr. Leader, collaborate with business leaders and/or analysts to provide analytical thought leadership and support for business problems. Help 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.
- Master's degree
- 1 to 3 years of relevant experience required
- Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
- Competence 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.
- 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.
- Ph.D.
- Degree in Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.)
- Experience with big data technologies which may include Hadoop, Cloud Computing Environments (including container creation, management & deployment), Spark, Dataiku, Amazon SageMaker etc.
- Background in asset management or financial services.
Vacancy posted 2 days ago
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