Title: Data Scientist Senior - Model Development Location: PHOENIX Arizona United States Type: Full-Time Job Description: 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. This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week. Relocation assistance is 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. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). 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.

Title: Data Scientist Lead - Model Development Location: COLORADO SPRINGS Colorado United States Type: Full-Time Job Description: 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 Data Scientist Lead will work closely with the Data Science Director to ensure that AI/ML modeling solutions are successfully developed and implemented. This will involve supervising multiple projects/initiatives, providing technical expertise, ensuring quality results, and mentor and leading Senior and Junior Data Scientists. Through cross-team collaboration, the lead works to understand business problems to formulate and coordinate AI/ML solutions in the Consumer Lending, Bank Operations, and Automation space. A Lead Data Scientist is expected to have a consulting mentality and be a subject matter expert in model building, communication, and leadership. This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week. Relocation assistance is available for this position. What you'll do: - Gathers, interprets, and manipulates complex structured and unstructured data to enable advanced analytical solutions for the business. - Leads and conducts advanced analytics leveraging machine learning, simulation, and optimization to deliver business insights and achieve business objectives. - Guides team on selecting 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 peer reviews technical documents for knowledge persistence, risk management, and technical review audiences. - Partners with business leaders from across the organization to proactively identify business needs and proposes/recommends analytical and modeling projects to generate business value. Works with business and analytics leaders to prioritize analytics and highly complex modeling. problems/research efforts. - Leads efforts to build and maintain 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. - Assists team with translating business request(s) into specific analytical questions, executing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations. - Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed. - Establishes and maintains 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. - Interacts with internal and external peers and management to maintain expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. - Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills. - Participates in enterprise-level efforts to 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. - 8 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 6 years of experience in predictive analytics or data analysis. - 6 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. - Expert ability to write 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. - Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics. - Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts. - Project management experience that demonstrates the ability to anticipate and appropriately manage project milestones, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation. - Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, forest models, etc. - Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc. - Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building. - Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science. - A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent). - Extensive technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization. What sets you apart: - Extensive model building experience (preferably in banking) covering a variety of AI/ML and traditional statistical modeling approaches. - Extensive hands-on experience preparing data and code for modeling. - Experience with the entire model lifecycle, including conceptualization, development, implementation, validation, and ongoing performance monitoring. - Experience working directly with clients, customers, or internal business partners. - Experience leading client or customer relationships and expectations, including senior leadership. Compensation range: The salary range for this position is: $164,780 - $314,960. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). 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.

🚗 Why Jerry.ai - Join a profitable pre-IPO startup with capital, traction, and runway ($240M funded | 60X revenue growth in 5 years | $2T market size) - Work closely with brilliant leaders and teammates from companies like Amazon, Better, LinkedIn, McKinsey, BCG, Bain - Disrupt a massive market and take us to a $10B business in the next few years - Our growth is driven by forward-thinking technology: Jerry.ai is getting mentioned in many conversations about our use of GenAI, such as this Forbes article - Be immersed in a talent-dense environment and greatly accelerate your career growth - Impact millions of users experience with car maintenance and auto insurance 💻 About the opportunity We are looking for a detail-obsessed Applied Data Scientist to join our growing team. The ideal candidate is passionate about the foundational layer of all data analysis: ensuring our data is clean, accurate, and reliable. You are a detective at heart, driven by a deep curiosity to understand complex data systems, and someone who finds immense satisfaction in transforming messy, ambiguous datasets into pristine assets that drive critical business decisions. This role is perfect for a scientist who wants to own the entire journey: from taking raw application data to generating clean inputs, to building models and delivering tangible value in real-world applications. You will be a central point of contact, communicating with engineers, product managers, and business analysts to ensure data integrity from collection to analysis. 🫵 How you will make an impact - Model Ownership: Participate in the full modeling lifecycle, from statistical analysis and experimentation to building, validating, and iterating on machine learning models that address critical business challenges - Data Quality: Own the data foundation by preparing, cleaning and transforming raw, complex data into high-quality features for modeling. Proactively identify and handle missing values, outliers, and inconsistencies - Problem Investigation: Investigate data discrepancies (tracking bugs, ETL errors, definitional issues) and design automated frameworks to ensure data accuracy - Cross-Functional Collaboration: Act as a strategic liaison, collaborating with data Engineering and product teams to drive the data strategy and definition of our centralized feature store, ensuring it becomes the 'single source of truth' for all ML models - Documentation: Create and maintain clear, authoritative documentation for data sources, cleaning processes, and variable definitions 🔎 Who You Are - Obsessed with Details: You have an exceptional eye for detail and a low tolerance for errors. You believe that accuracy and precision are non-negotiable - A Strategic Thinker: You can see the bigger picture and are passionate about building robust systems and processes that will stand the test of time - Proactive & Persistent: You don't wait for problems to find you. You actively seek out data quality issues and are persistent in seeing an investigation through to its resolution. - Curious & Adaptive: You are inherently curious and possess a strong desire to understand how things work. You're comfortable with ambiguity and skilled at breaking down complex problems 🚀 Requirements - Education: Bachelor’s degree (PhD preferred) in a quantitative field (Statistics, Physics, Mathematics, etc.) - Programming: Strong proficiency in Python (Pandas/NumPy) and SQL for complex querying and data manipulation - Data Quality: Hands-on experience with data cleaning techniques and data validation frameworks - Tooling: Familiarity with data visualization tools to help identify and communicate data issues While we appreciate your interest and application, only applicants under consideration will be contacted. Jerry.ai is proud to be an Equal Employment Opportunity employer. We prohibit discrimination based on race, religion, color, national origin, sex, pregnancy, reproductive health decisions or related medical conditions, sexual orientation, gender identity, gender expression, age, veteran status, disability, genetic information, or other characteristics protected by applicable local, state or federal laws. Jerry.ai is committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at recruiting@jerry.ai The successful candidate’s starting pay will fall within the pay range listed on this job posting, determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation may include opportunities for equity grants. We offer a comprehensive benefits package to regular employees, including health, dental, and vision coverage, paid time off, paid parental leave, 401(K) plan with employer matching, and wellness benefits, among others. Equity opportunities may also be part of your total rewards package. Part-time, contract, or freelance roles may not be eligible for certain benefits. About Jerry.ai: Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. From car insurance and financing to maintenance and safety, Jerry.ai does it all. We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers — and we’re just getting started. Jerry.ai was founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that’s disrupting a massive market.

• Define technical strategy and architect enterprise AI capabilities • Lead innovation and advance the state of healthcare AI • Influence organizational direction and technology decisions • Establish technical excellence standards across the organization • Build external recognition and strategic partnerships