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    Data Scientist Lead - Tampa, United States - USAA

    USAA
    USAA background
    Full time
    Description

    The Opportunity

    As Data Scientist Lead - Risk Data and Analytics, you will be responsible for developing AI models using machine learning, deep learning, and natural language processing, particularly transformer models and Generative AI. Your expertise will be instrumental in developing and implementing predictive modeling solutions for the risk and compliance organization, enabling them to proactively identify and mitigate risks. Furthermore, you will be responsible for comprehensive documentation of these models to facilitate internal validation processes and provide implementation support.

    We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position.

    What you'll do:

  • Design and implement data mining and natural language processing (NLP) algorithms, including Generative AI models, to extract valuable information from unstructured text data.
  • Develop machine learning models for forecasting, regression, classification, clustering, and advanced statistical analysis.
  • 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 clear and based on the highest quality data.
  • Assists team with translating business request(s) into specific analytical questions, performing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
  • Manages project portfolio achievements, risks, and impediments. Anticipates potential issues that could limit project success or implementation and advances as needed.
  • Establishes and maintains standard processes 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 groundbreaking 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, discernment, 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 subject area; 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 (12 years total experience).
  • 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 field and 6 years of experience in predictive analytics or data analysis.
  • 6 years proven experience in training and validating machine learning, statistical, physical, and other advanced analytics models.
  • 4 years of demonstrated ability in one or more dynamic scripted language (such as Python) for performing statistical analyses and/or building and scoring AI/ML models.
  • Experienced 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, etc.
  • Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
  • Validated ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
  • Project management experience that demonstrates the ability to anticipate and appropriately handle project achievements, risks, and impediments.
  • 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.
  • Advanced level of 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.
  • Proven track record 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 consistent track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
  • Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization.
  • What sets you apart:

  • Strong experience using transformer methods to build NLP models which extract pertinent information from unstructured text.
  • Strong experience in technical writing, specifically with preparing detailed AI model documentation.
  • Solid experience working with risk and compliance data in financial services.
  • Proficient experience with Generative AI models.
  • 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: $158, $303,830.00 .

    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.



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