Data Scientist Intermediate

Why USAA?

Let’s do something that really matters.

At USAA, we have an important mission: facilitating the financial security of millions of U.S. military members and their families. Not all of our employees served in our nation’s military, but we all share in the mission to give back to those who did. We’re working as one to build a great experience and make a real impact for our members.

We believe in our core values of honesty, integrity, loyalty and service. They’re what guides everything we do – from how we treat our members to how we treat each other. Come be a part of what makes us so special!

The Opportunity

As a dedicated Data Scientist Intermediate, you will work in the economic forecasting team responsible for producing economic forecast and macro update across the Enterprise.

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position will be based in our Charlotte, NC location.

Relocation assistance is not available for this position.

What you'll do:

• Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.
• 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 technical documents for knowledge persistence, risk management, and technical review audiences. Consults with peers for guidance, as needed.
• Translates business request(s) into specific analytical questions, executing on the analysis and/or modeling, and communicating outcomes to non-technical business colleagues.
• Consults with Data Engineering, IT, the business, and other internal stakeholders to deploy analytical solutions that are aligned with the customer’s vision and specifications and consistent with modeling best practices and model risk management standards.
• Seeks opportunities and materials to learn new techniques, technologies, and methodologies.
• 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.
• 2 years of experience in 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
• Experience in training and validating statistical, physical, machine learning, and other advanced analytics models.
• 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.
• Ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
• Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
• 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.
• Familiarity with performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• 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 with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
• Ability to communicate analytical and modeling results to non-technical business partners.

What sets you apart:

• Economics background
• Experience with R, Python and other data management and visualization tools
• Economic forecasting or experience with model management process.

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.

What we offer:

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. The salary range for this position is: $89,990 - $172,000.

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

For more details on our outstanding benefits, please 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.