Senior Data Scientist – Responsible AI

Job Title: Senior Data Scientist – Responsible AI

Location: Remote - United States

Type: Full Time

Our client is looking for a Senior Data Scientist – Responsible AI (RAI) function, playing a critical role as an individual contributor. This position works closely with multiple AI delivery teams in a matrixed setup, ensuring AI and Generative AI solutions are trustworthy, transparent, and aligned with responsible design principles. The focus is on building robust evaluation frameworks, analyzing model behavior, and embedding Responsible AI practices into real-world systems.

Key Responsibilities

• Drive the assessment and validation of AI/ML and GenAI models, focusing on risks such as hallucination, bias, lack of robustness, and explainability gaps.
• Develop scalable evaluation frameworks, reusable test datasets, and standardized procedures to measure model performance and behavior.
• Partner with AI product and engineering teams to integrate responsible AI metrics, guardrails, and evaluation mechanisms into development workflows.
• Convert experimental research and insights into production-ready evaluation tools and methodologies.
• Collaborate with engineering and QA teams to align validation approaches with CI/CD pipelines and release processes.
• Create and maintain documentation such as model cards, evaluation reports, and transparency artefacts to support governance requirements.
• Act as a subject matter advisor on Responsible AI for stakeholders across product, engineering, legal, risk, and compliance teams.
• Mentor team members on experimental design, evaluation best practices, and ethical AI considerations.

Required Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related discipline (or equivalent practical experience).
• Minimum of 6 years of hands-on experience in data science roles.
• Proven experience building, deploying, or evaluating machine learning models in real-world environments.
• Strong expertise in statistical methods, experimental design, and model evaluation techniques.
• Experience collaborating in agile, cross-functional environments with engineering and product teams.
• Proficiency in Python and SQL for data analysis and implementation of evaluation pipelines.
• Familiarity with cloud ecosystems such as AWS.
• Excellent communication skills with the ability to work effectively in a collaborative, matrixed organization.

Technical Environment

• Cloud platforms (e.g., AWS) with exposure to managed AI/ML services
• Data storage solutions including relational and NoSQL systems
• Data visualization and reporting tools such as Tableau, Power BI, or similar
• Agile collaboration tools supporting cross-functional delivery

Risk & Responsible AI Focus

• Contribute to embedding security and Responsible AI principles into the design and evaluation of AI systems
• Work closely with security, risk, and governance teams to identify and mitigate potential AI-related risks
• Support evolving compliance and governance requirements through structured evaluation and reporting

Preferred Experience

• Hands-on experience working with Generative AI or large language models
• Exposure to fairness analysis, explainability techniques, robustness testing, or hallucination detection
• Familiarity with Responsible AI frameworks, policies, or model governance practices
• Ability to operationalize research concepts into scalable, production-grade workflows