Data Science Manager

Job Description - Data Science Manager (260000TB)

Hyundai Capital America (HCA) helps people move forward. Through Hyundai Motor Finance, Genesis Finance, and Kia Finance, we deliver innovative financing, leasing, and insurance solutions to more than 3 million customers and businesses nationwide.

We’re a company driven by growth, innovation, and people. At HCA, you’ll find opportunities to build new skills, expand your career, and make a real impact—while working in a diverse, inclusive, and values‑driven environment. We’re proud to support our communities through volunteerism, philanthropy, and engaged Employee Resource Groups.

The Data Science Manager is an experienced individual contributor who independently builds, validates and deploys machine learning, AI and statistical models that support business needs across the enterprise. Working under general direction, the role owns assigned AI solutions from problem framing and data preparation through model development, evaluation and production, applying LLM-based and agentic AI techniques alongside traditional machine learning. The role partners with business, product, technology, AI governance, security and compliance teams to deliver well-governed solutions with measurable results.

Design, develop and deploy machine learning, AI and statistical models for assigned business problems; define success metrics with business partners and measure impact through testing and analysis.

Build and evaluate LLM-based and agentic AI solutions, including retrieval-augmented generation and AI agents, applying established evaluation, guardrail and quality standards.

Deploy models into production and maintain their performance, including training and inference pipelines, versioning, and monitoring for drift and accuracy.

Partner with business, product and technology teams, AI architecture and governance, security and compliance to scope use cases, access data, document solutions for the AI catalogue, and meet responsible-AI and regulatory requirements.

Contribute to team modeling standards and reusable patterns, conduct peer code and model reviews, and provide technical guidance as needed.

5-7 years of hands‑on experience building machine learning, AI and statistical models and deploying them to production including building LLM‑based or agentic AI solutions; equivalent project experience may be considered.

Experience independently managing projects or work streams of moderate scope and complexity.

Automotive or financial services industry experience preferred.

Bachelor’s degree in Data Science or AI, Computer Science, Statistics, Mathematics, Engineering or a related quantitative discipline; equivalent related work experience may be considered.

Master’s degree in a quantitative field preferred.

Thorough working knowledge of applied machine learning, AI and statistics, including model design, evaluation and validation.

Working experience with LLMs, agent development, retrieval-augmented generation, tool calling, and AI evaluation and guardrails.

Proficiency in Python, PySpark and SQL, and common machine learning and LLM application frameworks.

Experience building and deploying models on AWS (Sage Maker, Bedrock) or a similar cloud platform, with working knowledge of MLOps/LLMOps/Agent Ops practices such as model registry and monitoring.

Ability to translate business problems into well‑scoped data science solutions and explain model results and limitations to non‑technical stakeholders.

Understanding of responsible AI and model governance practices in a regulated environment.

Strong analytical, communication and…