Data Scientist Senior

USAA • Plano, TX

3d • Remote

About The Position

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 Employer: United Services Automobile Association Tasks: 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. May telecommute.

Requirements

• Will accept a Bachelor’s degree in Mathematics, Computer Science, Statistics, Economics, Finance, Actuarial Sciences, Science and Engineering or related field and 4 years of experience in the job offered or in a related occupation. Alternatively, will accept a Master’s degree in Mathematics, Computer Science, Statistics, Economics, Finance, Actuarial Sciences, Science and Engineering or related field and 12 months of experience in the job offered or in a related occupation.
• Calculus: Derivatives, Gradients, and Optimization Algorithms
• Linear Algebra: Linear Transformations and Matrix Decompositions
• Probability & Statistics: Descriptive Statistics, Probability Distributions, Hypothesis Testing, Stochastic Processes, and Monte Carlo Simulation
• Supervised Learning: Regression and Classification
• Unsupervised Learning: Clustering, Dimensionality Reduction, and Anomaly Detection
• Time Series Analysis
• Causal Inference
• Deep Learning Framework: TensorFlow, PyTorch, or Keras
• Deep Learning Architectures: CNNs, RNNs, Encoder-decoders, and Transformers
• NLP Experience: Embedding, Sentiment Analysis, Text Classification, and Topic Modeling
• LLM Experience: Use LLM for Summarization, Information Extraction, Text Generation, and Question Answering
• LLM Techniques: Embedding, Prompt Engineering, Retrieval Augmented Generation, and Fine-tuning
• 13.LLM Evaluation Metrics and Frameworks
• Python, PySpark, C++, SQL, and Power BI
• Git Version Control System
• Airflow CI/CD Tool
• Docker Containerization Tool
• Google Cloud Platforms, experience with Big Query, Vertex AI, and Cloud Storage
• Finance & Insurance Knowledge
• Data Science Development Platforms
• Multi-Cloud Data Platforms

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 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.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level