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Data Scientist Senior

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. Be part of what truly makes us special and impactful.

The Opportunity

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.

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. This position can also work remotely in the continental U.S. with occasional business travel. Relocation assistance is not available for this position.

What you'll do:

  • 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. Works with business and analytics leaders to prioritize analytics and modeling problems/research efforts.
  • 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.

What you have:

  • Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
  • 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.
  • Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
  • 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.
  • Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, 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.

What sets you apart:

  • Medium or large bank experience.
  • Strong knowledge of Python and/or SAS.
  • Control partner collaboration experience.
  • Knowledge of Model Risk Management, Model Governance, and Regulatory requirements.

Compensation range: The salary range for this position is: $143,320 - $273,930 .

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. The actual salary for this role may vary by location.

 

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

 

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. Additionally, our career path planning and continuing education assists employees with their professional goals.

 

For more details on our outstanding benefits, visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

 

USAA is an Equal Opportunity Employer. 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.

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Average salary estimate

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$143320K
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What You Should Know About Data Scientist Senior, USAA

Are you ready to take your data science skills to new heights? Join USAA as a Senior Data Scientist and be a part of a mission-driven team that empowers the military community to achieve financial security. In this dynamic role, you will dive deep into advanced analytics and machine learning, transforming complex business problems into actionable insights. Whether you're developing models for credit risk or optimizing everyday banking experiences, you'll make a significant impact. Collaborating closely with engineering partners, you'll deliver scalable solutions that enhance customer-facing applications, all while honing your skills and sharing your knowledge with junior scientists. At USAA, we value a culture that emphasizes honesty, integrity, loyalty, and service, making this a truly rewarding place to grow your career. Nestled in beautiful Colorado Springs, CO, or other strategic locations, this role offers a flexible work environment and you can even work remotely from anywhere in the continental U.S. Join us and help shape the future of financial services with innovative data-driven strategies.

Frequently Asked Questions (FAQs) for Data Scientist Senior Role at USAA
What responsibilities does a Senior Data Scientist have at USAA?

As a Senior Data Scientist at USAA, you will be responsible for translating complex business challenges into statistical, machine learning, and optimization solutions. This involves gathering and manipulating both structured and unstructured data to develop scalable analytical solutions that inform business decisions. You will work collaboratively with engineers to deliver impactful customer-facing applications and maintain a library of reusable algorithms. Additionally, you will mentor junior data scientists, ensuring a culture of learning and collaboration.

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What qualifications are required for the Senior Data Scientist position at USAA?

To qualify for the Senior Data Scientist role at USAA, candidates should hold at least a bachelor’s degree in a quantitative field such as mathematics, computer science, or statistics, or possess equivalent experience. A minimum of six years of predictive analytics experience is expected, alongside proficiency in programming languages like Python or R, and a strong capability in working with large datasets. Advanced degrees in related fields, coupled with experience in model training and validation, are also favorable.

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What technical skills are preferred for a Senior Data Scientist at USAA?

Ideal candidates for the Senior Data Scientist position at USAA should have robust experience in querying and preprocessing data, utilizing languages like SQL. Additionally, expertise in machine learning techniques for both supervised and unsupervised modeling, as well as familiarity with regulatory expectations surrounding model risk management, are crucial. Experience in deploying analytical models and communicating results to non-technical audiences will also set you apart.

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How does USAA support professional growth for Senior Data Scientists?

USAA is committed to the professional development of its employees, particularly Senior Data Scientists. The organization offers comprehensive career path planning, access to continuing education, and mentorship opportunities. Employees are encouraged to stay updated on cutting-edge techniques and methodologies in data science, ensuring that their skills remain competitive in an ever-evolving field. The supportive culture fosters collaboration and knowledge-sharing, essential for growth.

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What is the work environment like for a Senior Data Scientist at USAA?

The work environment for a Senior Data Scientist at USAA is both flexible and dynamic. While remote work is possible from the continental U.S., there is an expectation to be in the office four days a week. The culture is built around core values of integrity, loyalty, and service, creating a collaborative and supportive atmosphere. This role requires the ability to navigate complex projects while fostering a sense of community among fellow data scientists.

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Common Interview Questions for Data Scientist Senior
Can you explain a time when you developed a predictive model and its impact?

In your response, outline a specific project where you implemented a predictive model. Detail the data you used, the methodologies you applied, and the results or business decisions that stemmed from your model. Emphasize the impact on business performance or efficiency.

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What statistical techniques are you most comfortable with?

Discuss your familiarity with various statistical techniques relevant to the role, such as linear regression, logistic regression, decision trees, or clustering algorithms. Provide examples of where you have applied these techniques in professional settings.

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How do you handle unstructured data in your analyses?

Explain your approach to processing unstructured data, mentioning any tools or languages you have used. Discuss your experience in transforming unstructured data into actionable insights, highlighting a particular experience where this was crucial.

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Describe your experience with model validation?

Discuss a structured approach to model validation you have used, covering components such as performance metrics, overfitting avoidance, and robustness checks. Providing examples of how you validated models prior to implementation will illustrate your expertise.

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What is your process for selecting the right modeling technique for a given problem?

Share your decision-making process, starting from understanding the business need, through data exploration, to evaluating the performance of different algorithms based on specific criteria such as accuracy, interpretability, and computational efficiency.

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How do you ensure the transparency of your code?

Emphasize the importance of clean code in your work. Explain your practices, such as writing descriptive comments, employing clear variable naming conventions, and using version control systems to maintain transparent code that others can understand and build upon.

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What challenges have you faced when working with large datasets?

Describe specific challenges encountered while handling large datasets, such as memory constraints or data quality issues, and how you overcame those challenges. Highlight any tools or techniques that assisted in your problem-solving.

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Discuss an experience working collaboratively with engineers to deploy a model.

Provide detailed insights into a collaborative project where you worked with engineers to deploy an analytical model. Describe the communication, tools, and technologies used during the process to ensure successful deployment and user adoption.

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How do you keep up with the latest trends and technologies in data science?

Discuss your commitment to continuous learning—mention courses, online resources, conferences, or communities you participate in. Illustrating your proactive approach in expanding your knowledge will reflect your passion and dedication to the field.

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What experience do you have mentoring others in data science?

Share your mentoring experiences, focusing on ways you have guided junior data scientists in their projects. Discuss the techniques you used to support their development and the specific outcomes that resulted from your mentorship.

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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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March 26, 2025

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