Data Scientist Manager Data Scientist Manager …

Ameriprise Financial, Inc.
in Minneapolis, MN, United States
Permanent, Full time
Be the first to apply
Competitive
Ameriprise Financial, Inc.
in Minneapolis, MN, United States
Permanent, Full time
Be the first to apply
Competitive
Data Scientist Manager
Job Description

Are you passionate about Advanced Analytics? If so, we have an exciting opportunity to join our Fortune 500 company as a Data Scientist Manager! In this role, you will work with a high performing team of experienced data scientists, playing an integral role supporting business priorities. You will use advanced analytics techniques including predictive modeling, clustering, recommendation algorithms, and attribution analysis. You will translate modeling/analytic output into actionable business knowledge, insight and applications. There will also be opportunities to demonstrate your strong technical/problem solving skills while working collaboratively in a fast-paced team environment.

Responsibilities

  • Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, etc..
  • Under direction of the Sr. Leader, collaborate with business leaders 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.


Required Qualifications

  • Masters degree in a relevant field (statistics, applied mathematics, data science, etc.) or equivalent
  • 3-5 years relevant experience.
  • 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 a non-technical audience.
  • 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

Experience with big data technologies such as Dataiku and SageMaker.

About Our Company

With the right company, life can Be Brilliant®. At Ameriprise Financial, we're not just in the business of helping clients with their financial goals - we also help our advisors and employees reach their true potential by embracing an inclusive and collaborative culture. We celebrate the unique qualities and reward the contributions of our talented, passionate employees. If you're motivated and want to work for a strong, ethical company that cares about you and your community, take the next step with Ameriprise Financial and we can Be Brilliant® together.

Ameriprise Financial is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, national origin, genetic information, age, sexual orientation, citizenship, gender identity, disability, veteran status, marital status, family status or any other basis prohibited by law.
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