Principal - Data Scientist - AI

Position: Principal - Data Scientist - Responsible AI
General information

Career area

Technology

Work Location(s)

601 S. Tryon Street, NC

Remote?

No

#

21581

Posted Date

01-29-26

Working time

Full time

Ally and Your Career

Ally Financial only succeeds when its people do - and that's more than some cliché people put on job postings. We live this stuff! We see our people as, well, people - with interests, families, friends, dreams, and causes that are all important to them. Our focus is on the health and safety of our teammates as well as work-life balance and diversity and inclusion.

From generous benefits to a variety of employee resource groups, we strive to build paths that encourage employees to stretch themselves professionally. We want to help you grow, develop, and learn new things. You're constantly evolving, so shouldn't your opportunities be, too?

Work Schedule:

Ally designates roles as (1) fully on-site, (2) hybrid, or (3) fully remote. Hybrid roles are generally expected to be in the office a certain number of days per week as indicated by your manager. Your hiring manager will discuss this role's specific work requirements with you during the hiring process. All work requirements are subject to change at any time based on leader discretion and/or business need.

The Opportunity

As a leader in digital financial services, our customer and employee experiences are powered by data and AI. Our cloud-based data, analytics, and GenAI platform enables thousands of employees to make data-driven decisions every day. We are seeking skilled Data Scientists to support enterprise initiatives spanning machine learning, generative AI, and Responsible AI, helping deliver solutions that drive revenue, enhance user experience, and ensure AI systems operate safely and securely.

In this role, you will build, test, and deploy machine learning, generative AI, and agent-based solutions end to end. You will develop GenAI workflows such as prompt-driven systems, tool-calling agents, and evaluation pipelines, while also owning Responsible AI execution across the lifecycle. This includes identifying and resolving issues related to data usage, bias, model risk, evaluation quality, and release readiness. You will partner closely with business, engineering, and risk teams to turn Responsible AI requirements into practical development and validation standards, ensuring AI solutions are production-ready, compliant, and scalable.

At this time, Ally will not sponsor a new applicant for employment authorization for this position.

The Work Itself

* Lead experimentation initiatives, leveraging A/B testing, and novel AI approaches to continuously improve model performance and business outcomes.

* Advance responsible AI practices by integrating governance, ethical considerations, and security into every stage of model development and deployment.

* Develop and maintain trustworthy benchmarks and operational performance monitoring for predictive models and GenAI and agentic systems.

* Incorporate sophisticated algorithms, experimental design, and emerging AI methodologies to solve real-world challenges and push the boundaries of innovation.

* Identify and champion new business opportunities by proposing and delivering innovative AI-driven solutions that create tangible value and competitive advantage.

The Skills You Bring

Required:

* 5+ years of experience in machine learning and data science, with demonstrated impact in applied, real-world systems.

* Bachelor's degree in a quantitative or technical field (Computer Science, Engineering, Mathematics, Statistics, or similar).

* Strong coding skills in Python, with experience building maintainable, production-grade ML/AI systems.

* Experience working in cloud data and ML platforms such as AWS, Snowflake, Sage Maker, or equivalent environments.

* Experience influencing technical direction beyond individual projects, including setting best practices, mentoring others, and driving alignment across teams.

* Ability to proactively identify risks and gaps in AI systems (e.g., reliability, bias, safety, explainability, monitoring) and drive pragmatic solutions at scale.

Nice-to-Haves:

* Graduate degree (MS or PhD) in a relevant field.

* Hands-on GenAI, agent, and ML…