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About the Role
Support modeling, data analysis, campaign execution, and database needs for Columbia Threadneedle Investments Asset Management. Manage large data sets, providing information-based decision logic and predictive modeling solutions, and translate modeling/analytic output into understandable/actionable business knowledge, insight and applications.
Responsibilities
- Assist in the development and implementation of complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, etc., for marketing and risk management purposes.
- May lead efforts on small-medium sized projects.
- Assist in dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, 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.
- Partner closely with leader and others to ensure proper delivery.
- Consult and coordinate campaign execution for direct to client campaigns.
- Assist in identifying and executing targeting and optimization opportunities.
- 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.
- 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.
Requirements
- 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, etc..
- Applicants must have a valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States (e.g., H-1B, F-1 CPT, F-1 OPT, TN).
Skills
- predictive modeling
- advanced machine learning techniques
- simulation
- optimization solutions
- data extraction
- derived and dependent variable creation
- data quality control
- targeting
- optimization
- analytical thought leadership
- business-driven analytic solutions
- data governance
- advanced statistical concepts
- linear algebra
- generalized regression models
- Bayesian methods
- random forest
- gradient boosting
- neural networks
- machine learning
- clustering
- SAS
- R
- Python
- SQL
- data visualization
- strategic techniques
- analytic techniques
- big data technologies
- Hadoop
- Cloud Computing Environments
- Spark
Location
- United States
Work Type
- Hybrid
- Full-time
Experience Level
- Senior
- 1 to 3 years
Education Level
- Master's degree
- Ph.D. Degree in Quantitative Discipline
Salary/Compensations
- $78,700 - $138,200
Benefits
- Vacation time
- Sick time
- 401(k)
- Health insurance
- Dental insurance
- Life insurance
About the 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.
Equal Opportunity
- Ameriprise Financial is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, ancestry, age, physical or mental disability, medical condition, pregnancy, military status, veteran status, genetic information, citizenship, disability status, marital status, family status or any other basis prohibited by law.
- We are committed to fostering an inclusive and accessible recruitment process for individuals with disabilities. If you require a reasonable accommodation to participate in the application or interview process, speak to your recruiter to discuss how we can support you.