Data Scientist (Mid Level)

About The Company

USAA is a leading financial services organization dedicated to serving the military community and their families. Our mission is to empower our members to achieve financial security through highly competitive products, exceptional service, and trusted advice. We pride ourselves on fostering a culture rooted in core values such as honesty, integrity, loyalty, and service, which guide our interactions with members and each other. USAA is committed to making a meaningful impact by providing innovative solutions tailored to the unique needs of the military community. We also support active-duty military spouses, offering flexible work arrangements including remote or hybrid options where applicable, to promote work-life balance and inclusivity.

About The Role

We are seeking a dedicated Data Scientist to join our team and drive data-driven decision-making across the organization. In this role, you will be responsible for translating complex business problems into advanced analytical solutions utilizing statistical methods, machine learning, simulation, and optimization techniques. Your work will directly influence business strategies by delivering scalable, automated models that enhance revenue, reduce expenses, and mitigate risks. Collaborating closely with engineering teams, you will develop and deploy analytical models within USAA's framework, ensuring they are robust, compliant, and aligned with business objectives. You will also contribute to expanding our internal library of algorithms and tools, supporting ongoing research and development efforts, and validating models through rigorous risk management processes. This position requires a proactive individual capable of working in a collaborative environment, maintaining awareness of the latest technological advancements, and communicating complex findings to non-technical stakeholders.

This role offers a flexible work environment requiring in-office presence four days per week. The position can be based in San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Please note that relocation assistance is not provided for this role.

Qualifications

• Bachelor's degree in Mathematics, Computer Science, Statistics, Economics, Finance, Actuarial Science, Science, Engineering, or a related quantitative field, or equivalent experience (4+ years).
• At least 4 years of experience in predictive analytics or data analysis, or an advanced degree (Master's or PhD) with 2 years of relevant experience.
• Minimum of 2 years of experience in training and validating statistical, physical, machine learning, or advanced analytics models.
• Proficiency in scripting languages such as Python, R, or similar for statistical analysis and machine learning model development.
• Experience in querying and preprocessing data from structured, semi-structured, and unstructured sources using SQL, NoSQL, or similar query languages.
• Hands-on experience working with diverse data formats including JSON, XML, delimited files, images, and text documents.
• Strong understanding of classical supervised modeling techniques such as linear and logistic regression, decision trees, and ensemble methods, as well as unsupervised methods like clustering algorithms.
• Excellent communication skills with the ability to convey technical insights to non-technical audiences.
• Experience working within regulatory frameworks and understanding model risk management standards.

Responsibilities

• Gather, interpret, and manipulate both structured and unstructured data to facilitate advanced analytics solutions.
• Develop scalable, automated models using machine learning, simulation, and optimization techniques to generate actionable insights.
• Select appropriate modeling techniques considering data limitations, business needs, and application context.
• Deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) frameworks, ensuring compliance and robustness.
• Document technical processes and model details for knowledge sharing, risk management, and review purposes.
• Assess business needs to recommend analytical projects that add value and align with organizational goals.
• Collaborate with business and analytics leaders to prioritize research efforts and problem-solving initiatives.
• Contribute to building a library of reusable algorithms and supporting code to ensure transparency and high quality of models.
• Translate business questions into analytical tasks, execute analyses, and communicate findings with clear recommendations.
• Work closely with Data Engineering, IT, and other stakeholders to deploy models that meet business specifications and adhere to best practices.
• Stay informed about emerging techniques, tools, and methodologies in data science and analytics.
• Ensure all activities comply with risk, regulatory, and compliance policies, including effective risk identification and mitigation.

Benefits

• Comprehensive medical, dental, and vision insurance plans to support your health and well-being.
• 401(k) retirement plan with company matching contributions.
• Pension plan and life insurance options.
• Parental benefits and adoption assistance programs.
• Paid time off including holidays, plus 16 paid volunteer hours annually.
• Access to various wellness programs aimed at promoting physical, emotional, and financial wellness.
• Opportunities for career development, ongoing education, and professional growth.