Data Scientist
Netrolynx AI · United States
- Hybrid
- Full-time
- $150,000 / year
- United States
Job highlights
- Lead AI/GenAI evaluation for safety and fairness.
- Develop and implement repeatable AI evaluation workflows.
- Partner with AI teams on Responsible AI integration.
- Translate research into scalable evaluation capabilities.
- Mentor junior data scientists on AI evaluation.
About the 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
- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.
- 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.
- Strong foundation in experimental design, statistical analysis, and model evaluation methodology.
- Proficiency in Python and SQL for data analysis and evaluation workflows.
- Experience working with modern cloud platforms such as AWS.
- Excellent communication skills and the ability to operate effectively within a matrixed team model.
Responsibilities
- Lead evaluation and validation of AI and GenAI systems, including assessment of hallucination, fairness, robustness, explainability, and other model behavior risks.
- Design and implement repeatable evaluation workflows, benchmark datasets, and structured model behavior tests.
- Serve as the Responsible AI data science partner for assigned AI delivery teams, guiding the integration of RAI metrics, guardrails, and evaluation practices.
- Translate research findings and experimental methods into scalable, platform-ready evaluation capabilities.
- Collaborate with AI/ML engineers and QA analysts to align evaluation logic with testing pipelines and deployment workflows.
- Support the creation of model cards, evaluation documentation, and transparency artifacts required for governance and review.
- Provide Responsible AI consultation to product, engineering, risk, legal, and governance stakeholders.
- Mentor junior and mid-level data scientists on evaluation design, experimental rigor, and Responsible AI practices.
Benefits
- Medical, dental, vision, and life insurance
- Retirement savings - 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
- Tuition reimbursement up to $5,250/year
- Business-casual environment that includes the option to wear jeans
- Generous paid time off upon hire - including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
- Paid volunteer time - 16 hours per calendar year
- Leave of absence programs - including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
- Business Resource Groups (BRGs) - BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.
Equal Opportunity
We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age (40 and over), race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.
For remote and hybrid positions, you will be required to provide reliable high-speed internet with a wired connection as well as a dedicated workspace with limited disruptions. You must have reliable connectivity from an internet service provider that is fiber, cable, or DSL internet. Necessary computer equipment will be provided. You may be required to work in the office if you do not have an adequate home work environment and the required internet connection.
Key skills/competency
- Responsible AI
- Data Science
- Machine Learning
- GenAI
- Python
- SQL
- AWS
- Model Evaluation
- Experimental Design
- Statistical Analysis
Skills & topics
- Data Scientist
- Responsible AI
- AI Evaluation
- Machine Learning
- GenAI
- Python
- SQL
- AWS
- Statistical Analysis
- Experimental Design
How to get hired
- Tailor your resume: Highlight 6+ years of data science experience and AI/ML evaluation expertise. Emphasize Python, SQL, and AWS proficiency.
- Showcase RAI skills: Detail your experience with experimental design, statistical analysis, and model behavior assessment (hallucination, fairness, explainability).
- Prepare for technical interviews: Be ready to discuss your approach to evaluating AI systems and solving complex data science problems.
- Demonstrate collaboration: Highlight your experience working in matrixed teams and communicating technical concepts to diverse stakeholders.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the primary focus of the Senior Data Scientist, Responsible AI role at Netrolynx AI?
- The Senior Data Scientist, Responsible AI role at Netrolynx AI focuses on ensuring AI and GenAI systems are measurable, transparent, safe, and aligned with Responsible AI principles by embedding within AI delivery teams to lead evaluation methodology and model behavior analysis.
- What are the key technical skills required for the Senior Data Scientist, Responsible AI position?
- Key technical skills for this role include proficiency in Python and SQL for data analysis and evaluation, experience with cloud platforms like AWS, and a strong foundation in experimental design, statistical analysis, and model evaluation methodology.
- How does Netrolynx AI support work-life balance for its employees?
- Netrolynx AI supports work-life balance through a flexible work environment, fluid career paths, generous paid time off, paid volunteer time, and various leave of absence programs including paid parental leave.
- What is the minimum experience required for the Senior Data Scientist, Responsible AI role?
- The minimum experience required is 6+ years of professional data science experience, with a demonstrated expertise in developing or evaluating AI/ML systems in production or pre-production environments.
- What kind of AI systems will this Senior Data Scientist evaluate?
- This Senior Data Scientist will evaluate AI and GenAI systems, focusing on aspects like hallucination, fairness, robustness, and explainability to ensure they are safe and aligned with Responsible AI principles.
- Does Netrolynx AI offer remote work options for this Senior Data Scientist role?
- The job description mentions requirements for remote and hybrid positions, indicating that remote work may be an option. Candidates will need to ensure they meet the specified requirements for reliable high-speed internet and a dedicated workspace.
- What does 'Responsible AI' mean in the context of this role?
- In this context, Responsible AI (RAI) refers to the principles and practices that ensure AI systems are developed and deployed ethically, with a focus on safety, fairness, transparency, and accountability.
- What opportunities are there for mentorship within the Senior Data Scientist role?