Data Scientist

Company: Netrolynx AI

Location: Location not specified (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-06-27

About this role

About The Company
Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.


About The Role
The Senior Data Scientist of Responsible AI serves as a senior individual contributor within Empower's Responsible AI (RAI) team. This role embeds directly with multiple AI delivery teams as a matrixed partner, ensuring AI and GenAI systems are measurable, transparent, safe, and aligned with Responsible AI principles. The position focuses on evaluation methodology, model behavior analysis, and operationalizing Responsible AI practices in collaboration with engineering, QA, security, and governance partners.


Qualifications
Applicants should possess a Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience. Candidates should have a minimum of 6+ years of professional data science experience, with demonstrated expertise in developing or evaluating AI/ML systems in production or pre-production environments. A strong foundation in experimental design, statistical analysis, and model evaluation methodology is essential. Proficiency in Python and SQL for data analysis and evaluation workflows is required, along with experience working with modern cloud platforms such as AWS. Excellent communication skills and the ability to operate effectively within a matrixed team model are also necessary.


Responsibilities

  • Lead evaluation and validation of AI and GenAI systems, including assessment of hallucination, fairness, robustness, ...

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