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Data Scientist / Machine Learning Scientist

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. The Bank AI/ML team is looking to fill several Senior Data Science positions. Candidates with backgrounds in model development for credit risk, marketing, or everyday banking are preferred.As a dedicated Data Scientist Senior you will translate business problems into applied statistical, machine learning, simulation, and optimization solutions to advise actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. In collaboration with engineering partners, delivers solutions at scale, and enables customer-facing applications. Leverages database, cloud, and programming knowledge to build analytical modeling solutions using statistical and machine learning techniques. Collaborates with other data scientists to improve USAA’s tooling, growing the company’s library of internal packages and applications. Works with model risk management to validate the results and stability of models before being pushed to production at scale.This position can work remotely in the continental U.S. with occasional business travel.Gathers, interprets, and manipulates structured and unstructured data to enable advanced analytical solutions for the business.Develops scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.Composes, and assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences.Assesses business needs to propose/recommend analytical and modeling projects to add business value. Builds and maintains a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data.Translates complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations.Manages project milestones, risks, and impediments. Escalates potential issues that could limit project success or implementation.Develops best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards.Maintains expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.Serves as a mentor to junior data scientists in modeling, analytics, and computer science tasks.Participates in internal communities that drive the maintenance and transformation of data science technologies and culture.Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; 6 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master’s, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 4 years of experience in predictive analytics or data analysis.~4 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.~4 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.~ Proven experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).~ Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.~ Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.~ Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.~ Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.~ Experience guiding and mentoring junior technical staff in business interactions and model building.~ Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.Medium or large bank experience.Strong knowledge of Python and/or SAS.Knowledge of Model Risk Management, Model Governance, and Regulatory requirements.Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.About the Company:USAAIndustry leading service that puts our memberships' needs first.We're dedicated to the financial well-being of members of the military and their families for generations to come. That's why we provide a variety of financial products and best-in-class service to help our members achieve their financial goals and plan for the future.Our history continues to drive our purpose.USAA began in 1922 with 25 Army officers who offered to insure each other's vehicles when no one else would. Today, their tiny organization has grown into a respected institution offering a full range of financial products to millions of members.We believe they'd be pleased to know that USAA remains true to their founding values of service, loyalty, honesty and integrity.In 1922, when 25 Army officers met in San Antonio, Texas, and decided to insure each other's vehicles, they could not have imagined that their tiny organization would one day serve over 8 million members and become one of the only fully integrated financial services companies in America.We believe they would be pleased to know that USAA has remained true to their founding values of service, loyalty, honesty and integrity.Company Size:10,000 employees or moreIndustry:Financial ServicesFounded:1922Website:https://www.usaa.com
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What You Should Know About Data Scientist / Machine Learning Scientist, USAA

Join USAA as a Senior Data Scientist / Machine Learning Scientist in sunny Tampa, FL, and step into a pivotal role that empowers you to harness your passion for data to make a real difference in the lives of military families! At USAA, we pride ourselves on our mission to help our members achieve financial security through innovative products and exceptional service. In this role, you'll work closely with our Bank AI/ML team, where your expertise in machine learning and predictive analytics will help to solve complex business problems and drive actionable insights. Your days will be filled with gathering and interpreting both structured and unstructured data to develop cutting-edge models that optimize risk, reduce expenses, and enhance customer satisfaction. You'll collaborate with engineering partners to deploy analytical solutions at scale while continuously improving our internal tools and methodologies. Plus, this role isn’t just about numbers; you'll also mentor junior data scientists and contribute to our vibrant community. We’re looking for individuals with a strong foundation in statistical modeling and programming—think Python or R—to join us in this exciting journey. Embrace the flexibility of remote work while occasionally traveling for business to connect with your team. If you’re ready to take your career to the next level and impact our members' financial futures, come make a difference with us at USAA!

Frequently Asked Questions (FAQs) for Data Scientist / Machine Learning Scientist Role at USAA
What are the key responsibilities of a Senior Data Scientist / Machine Learning Scientist at USAA?

As a Senior Data Scientist / Machine Learning Scientist at USAA, your primary responsibilities include translating business problems into statistical and machine learning solutions, developing scalable models, and collaborating with engineering teams to implement these solutions effectively. You'll also be tasked with mentoring junior data scientists and continuously improving our analytics tooling while ensuring compliance with risk management standards.

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What qualifications are required for a Senior Data Scientist / Machine Learning Scientist position at USAA?

To qualify for the Senior Data Scientist / Machine Learning Scientist position at USAA, candidates typically need a Bachelor's degree in a quantitative discipline like mathematics or computer science along with six years of relevant experience in predictive analytics. Alternatively, an advanced degree (Master's or PhD) in a similar field with four years of experience is also acceptable. Proficiency in programming languages such as Python or R is crucial, as well as experience with statistical modeling techniques.

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What programming languages are preferred for a Senior Data Scientist / Machine Learning Scientist at USAA?

For the Senior Data Scientist / Machine Learning Scientist position at USAA, strong experience in dynamic scripted languages such as Python and R is preferred. Proficiency in SQL and familiarity with machine learning frameworks and technologies will also be beneficial in developing and deploying robust analytical models.

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What benefits does USAA offer to Senior Data Scientist / Machine Learning Scientist employees?

At USAA, Senior Data Scientists / Machine Learning Scientists enjoy comprehensive benefits including medical, dental, and vision plans, a 401(k) with company match, paid time off, parental leave, and wellness programs. Additionally, employees benefit from a culture that prioritizes their physical, emotional, and financial well-being.

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Is remote work possible for the Senior Data Scientist / Machine Learning Scientist role at USAA?

Yes, the Senior Data Scientist / Machine Learning Scientist position at USAA offers the flexibility to work remotely within the continental U.S. This arrangement is perfect for individuals seeking a work-life balance while still contributing meaningfully to our team and mission.

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Common Interview Questions for Data Scientist / Machine Learning Scientist
Can you describe your experience with statistical modeling for financial services?

When answering this question, detail specific projects where you applied modeling techniques to address financial problems. Highlight your thought process, the methodologies you implemented, and the outcomes that benefitted the organization. Be sure to connect how your work aligns with USAA’s mission.

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How do you ensure your machine learning models are scalable and maintainable?

In your response, focus on practices like code documentation, modular development, and utilizing version control systems. Discuss how these practices ensure your models can handle increased data loads while remaining easy to update and refine, thus enhancing long-term value.

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Describe a time when you had to communicate complex technical results to a non-technical audience.

Use the STAR (Situation, Task, Action, Result) format to outline your approach to simplification. Explain how you tailored your communication strategy, including visual aids or analogies, to ensure clarity and actionable insights were conveyed to stakeholders.

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What techniques do you use to assess the performance of your models?

Discuss various metrics you employ—like accuracy, precision, recall, or ROC-AUC scores—in the context of financial modeling. Explain how you validate models, including any specific tools or frameworks you utilize to ensure performance and compliance with regulations.

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Can you give an example of how you have mentored a junior data scientist?

Provide an example focusing on your mentoring style: how you approached teaching technical skills or facilitating professional development. Highlight the growth or accomplishments achieved by the mentee as a result of your guidance.

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What strategies do you employ to keep up with advancements in data science and machine learning?

Outline your commitment to continuous learning through online courses, attending conferences, participating in webinars, or engaging with data science communities. Emphasize your proactive approach to applying new techniques or methodologies in your work at USAA.

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How do you handle data privacy and compliance in your analyses?

Discuss specific regulations and compliance frameworks you've worked with that pertain to data privacy in the financial industry. Explain how you ensure your analytical processes adhere to these standards to safeguard member information.

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Describe a challenging data problem you faced and how you solved it.

Use a specific instance that highlights your analytical thinking and problem-solving skills. Detail the challenge, your approach, the tools you utilized, and the successful outcome that reinforced your ability to navigate complex data issues.

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What is your experience with deploying models into production?

Discuss your experience with model deployment, including specific platforms, monitoring strategies, and post-deployment evaluation procedures. Emphasize your familiarity with technologies that facilitate smooth transitions from model development to operational use.

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How do you prioritize and manage multiple data projects simultaneously?

Share your project management techniques, particularly any frameworks or tools you use to track progress, manage deadlines and ensure effective communication with other team members while maintaining high standards of work.

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Photo of the Rise User
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)

WHAT WE STAND FOR No matter how many years we’re in business or how many members we serve, our core mission and the values that inspired it never change. Our mission is to stand with our members and be there for them and their families by facili...

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Full-time, remote
DATE POSTED
April 22, 2025

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