Senior Data Scientist at U.S. Bank

Minneapolis, Minnesota, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Jun, 26

Salary

140900.0

Posted On

08 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Advanced Analytics, Python, SQL, Modeling, Cloud, Statistical Analysis, Predictive Modeling, Machine Learning, Data Integration, Data Visualization, Power BI, Tableau, Git, AWS, Azure

Industry

Banking

Description

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One. Job Description We’re looking for a data science / advanced analytics professional who enjoys turning fragmented, high‑volume data into clear insights, strong models, and measurable business outcomes. You’ll work on large analytics initiatives—acquiring and integrating data from multiple sources, building predictive and statistical models, and translating results into recommendations leaders can act on. If you like combining technical depth (Python/SQL, modeling, cloud) with strong communication and cross‑functional partnership—this is a great fit. What You’ll Do Lead large data and analytics projects that gather and integrate significant volumes of data across platforms and sources. Develop methods, processes, and systems to consolidate and analyze unstructured and diverse big data sources to generate insights and solutions for client services and product enhancement. Acquire data from multiple sources and perform analysis to answer complex business questions. Implement, validate, and maintain predictive and statistical models, with a focus on big data applications. Identify, analyze, and interpret trends/patterns in complex datasets to provide answers and recommend actions. Interpret data and analyze results using advanced statistical techniques and analytics tools. Present findings clearly and concisely, enabling stakeholders to quickly understand results, recommendations, and make data‑driven decisions. Collaborate with business and technical partners to prioritize requests and provide a holistic view of the analysis. Measure and monitor outcomes of applied recommendations and propose adjustments when needed. Ensure compliance with company standards for data acquisition, sharing, and the application of recommendations. Basic Qualifications Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience Six to eight years of relevant experience Preferred Skills & Experience Strong analytical foundation with experience working across large, complex datasets to identify trends, answer business questions, and inform decisions Hands‑on experience with advanced analytics, statistical analysis, and predictive modeling, including familiarity with core machine learning concepts Proficiency in Python for analysis and modeling, along with strong SQL skills across relational and non‑relational data sources Experience with data preparation, exploratory data analysis, and model evaluation, with attention to data quality and reliability Ability to translate analytical findings into clear insights and recommendations, supported by effective communication and data visualization Exposure to cloud‑based analytics environments (AWS and/or Azure), with interest in modern analytics capabilities including Generative AI Comfortable working in a collaborative, cross‑functional environment, managing priorities and contributing to multiple initiatives Experience with data visualization tools (Power BI, Tableau, or similar) and version control (e.g., Git) is a plus The role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days. This position is not eligible for visa sponsorship. If there’s anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our disability accommodations for applicants. Benefits: Our approach to benefits and total rewards considers our team members’ whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following: 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 Review our full benefits available by employment status here. U.S. Bank is an equal opportunity employer. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, and other factors protected under applicable law. E-Verify U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about the E-Verify program. The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements). Pay Range: $119,765.00 - $140,900.00 U.S. Bank will consider qualified applicants with arrest or conviction records for employment. U.S. Bank conducts background checks consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act as well as the San Francisco Fair Chance Ordinance. U.S. Bank is subject to, and conducts background checks consistent with the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA). In addition, certain positions may also be subject to the requirements of FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or federal guidelines applicable to an agreement, such as those related to ethics, safety, or operational procedures. Applicants must be able to comply with U.S. Bank policies and procedures including the Code of Ethics and Business Conduct and related workplace conduct and safety policies. Posting may be closed earlier due to high volume of applicants. At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Responsibilities

The role involves leading large data and analytics projects, gathering and integrating significant volumes of data across platforms and sources to generate insights and solutions. Responsibilities include developing methods for analyzing diverse big data sources, implementing predictive models, and translating findings into actionable recommendations for leaders.