Data Scientist (Multiple openings) in Minneapolis, MN.

U.S. Bank • Minneapolis, MN

2d • Onsite

About The Position

U.S. Bank is seeking a full-time Data Scientist (Multiple openings) in Minneapolis, MN. This role is responsible for delivering big data/analytics projects by collecting, cleaning, and pre-processing large-scale structured and unstructured datasets from multiple internal and external sources to ensure high-quality data for downstream analysis and model development. The Data Scientist will extract, collect, and organize complex datasets using SAS and SQL, and harvest publicly available data through Python-based web scraping. They will perform Exploratory Data Analysis (EDA) using statistical methods to identify, analyze, and interpret trends or patterns in complex data, addressing business questions and providing actionable recommendations. The role involves developing, building, and implementing predictive and statistical models, machine learning algorithms, and data mining techniques to generate insights and solutions on big data for client services and product enhancement. Additionally, the Data Scientist will build scalable, efficient, production-ready solutions, including model deployment, monitoring, and continuous improvement for banking applications. They will interpret data and analytical results using advanced statistical techniques (regression, correlation, clustering, hypothesis testing). Collaboration with cross-functional teams (product, customer experience, risk, compliance, and business) is key to delivering data-driven solutions and communicating insights clearly through storytelling, visualizations, and executive-ready summaries. Ensuring all data acquisition, solutions, and recommendations adhere to company’s security, privacy, and compliance standards is also a core responsibility. Uses the following tools and technologies: Python, R, SAS, SQL, DataRobot.

Requirements

• Bachelor’s degree or equivalent in Computer Science or Computer Engineering and 5 years (progressive, post-baccalaureate) experience in a software engineering or data science occupation.
• 24 months of experience with Extracting, collecting, and organizing complex datasets using SAS and SQL, and harvesting publicly available data through Python-based web scraping.
• 24 months of experience building predictive and machine learning models, performing data mining, and developing visualizations that translate large-scale data into actionable insights and business outcomes.
• 24 months of experience working with Python, R, SAS, and SQL to perform large-scale data extraction.
• 24 months of experience interpreting data and analytical results using advanced statistical techniques (regression, correlation, clustering, hypothesis testing).
• 24 months of experience leveraging AI platforms, including DataRobot, to support data-driven decision making.
• Employer will accept experience gained concurrently.

Responsibilities

• Responsible for delivering big data/analytics projects by collecting, cleaning, and pre-processing large-scale structured and unstructured datasets from multiple internal and external sources to ensure high-quality data for downstream analysis and model development.
• Extract, collect, and organize complex datasets using SAS and SQL, and harvesting publicly available data through Python-based web scraping.
• Perform Exploratory Data Analysis (EDA) using statistical methods to identify, analyze, and interpret trends or patterns in complex data.
• Address related business questions and provide actionable recommendations.
• Develop, build, and implement predictive and statistical models, machine learning algorithms, and data mining techniques to generate insights and solutions on big data for client services and product enhancement.
• Build scalable, efficient, production-ready solutions, including model deployment, monitoring, and continuous improvement for banking applications.
• Interpret data and analytical results using advanced statistical techniques (regression, correlation, clustering, hypothesis testing).
• Collaborate cross-functionally with product, customer experience, risk, compliance, and business teams to deliver data-driven solutions and communicate insights clearly.
• Present work to technical and non-technical stakeholders through clear storytelling, visualizations, and executive-ready summaries.
• Ensure all data acquisition, solutions and recommendations adhere to company’s security, privacy, and compliance standards.

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law
• Incentive and recognition programs
• Equity stock purchase
• Pension

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level