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USAA · 11 hours ago

Data Scientist Senior

San Antonio, TX

Full-time

Onsite

Senior Level

$143K/yr - $274K/yr

6+ years exp

USAA is dedicated to empowering its members to achieve financial security and is seeking a Senior Data Scientist to join their Insurance Data Science team. The role involves translating business problems into statistical and machine learning solutions, developing scalable analytical models, and collaborating with various teams to drive business value through data insights.

BankingFinancial ServicesInsuranceVenture Capital

No H1B

Responsibilities

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 visible and based on the highest quality data

Translates complex business request(s) into specific analytical questions, completes the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations

Handles project landmarks, risks, and impediments. Calls out potential issues that could limit project success or implementation

Develops standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling procedures and model risk management standards

Maintains expertise and awareness of pioneering 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

Qualification

Machine LearningStatistical AnalysisData ManipulationPredictive AnalyticsPythonSQLModel Risk ManagementData Engineering CollaborationCommunication SkillsMentoring

Required

Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; 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 field 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

Validated experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code visibility)

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

Preferred

Strong history of collaborating with other data scientists, data engineers, and IT on delivering AI/ML solutions to business partners in highly regulated environments, with a foundational understanding of Model Risk Management (MRM) and governance principles

Proficiency in software engineering standard methodologies for data science, including robust coding standards, version control, and collaboration with engineering teams for model deployment and productionization

Demonstrated history of partnering with business subject matter authorities to translate complex business problems into advanced analytical solutions, critically evaluating approaches, and translating technical findings into clear, business-oriented recommendations and driving adoption of data-driven strategies

Experience in the Life Insurance, Health Insurance, and/or Annuities business both digitally and in support of call center operations

Validated expertise in using analytics and modeling to drive marketing engagement and optimization, designing customer journeys, persona and segmentation, positioning and messaging optimization, using data to support go-to-market strategies, etc

Experience in user acceptance testing, pilot testing, experimentation, and/or A-B Testing to evaluate the value delivery of model solutions