Empower Retirement is looking for a Data Scientist to join our Responsible AI team. You will embed directly with AI Factory teams, ensuring AI and GenAI applications are safe, measurable, transparent, and aligned with our Responsible AI principles. This matrixed role involves executing evaluations, contributing to methodological development, and researching emerging techniques.
What You'll Do
- Serve as the Responsible AI data science partner for assigned AI CoreWorks Factory teams, supporting integration of evaluation workflows, guardrails, and measurement practices.
- Guide teams in applying Responsible AI platform capabilities, including real-time guardrails, hallucination scoring, explainability modules, and batch evaluation processes.
- Execute evaluations related to hallucination, fairness, contextual grounding, transparency, robustness, and other model behavior risks.
- Develop benchmark datasets, evaluation scripts, and structured testing methods that enable consistent assessment across AI applications.
- Analyze model architectures, data characteristics, and inference workflows to inform evaluation design and interpretation of results.
- Partner with QA teams to align evaluation outputs with testing thresholds, validation workflows, and platform guardrails.
- Apply machine learning, statistical, and experimental design techniques to assess model behavior and performance in applied contexts.
- Review and assess third-party or open-source models and tools from a safety, robustness, and evaluation perspective.
- Contribute to research, experimentation, and prototyping of emerging Responsible AI methods and evaluation techniques.
- Collaborate with AI/ML engineers to operationalize evaluation logic and integrate Responsible AI metrics into shared platforms.
- Assist with preparation of model cards, evaluation summaries, transparency documentation, and lineage records.
- Coordinate closely with global RAI data science partners to align methods, backlog priorities, and standards.
What We're Looking For
- Bachelor’s or Master’s degree in computer science, data science, statistics, or a related quantitative discipline, or equivalent experience.
- Experience developing, validating, or evaluating machine learning models in production or pre-production environments.
- Strong proficiency in Python and experience working with data for ML analysis, experimentation, and evaluation.
- Familiarity with experimental design, statistical analysis, and model performance assessment.
- Exposure to GenAI or LLM systems, including model behavior analysis, safety testing, or explainability techniques.
- Ability to collaborate effectively with engineering, QA, and product teams in a matrixed environment.
- Strong written and verbal communication skills.
Nice to Have
- Hands-on experience implementing evaluation techniques such as grounding checks, judge-model scoring, or explainability methods (for example SHAP or LIME).
- Familiarity with cloud-based ML environments or enterprise-scale AI systems.
- Interest in research related to Responsible AI, fairness, factuality, transparency, or model risk.
- Experience contributing to shared evaluation frameworks or analytical tooling.
Technical Stack
- Python
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, 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.
