Lead, Data and Model Ethics

About the Role

Key Responsibilities

• Partnering with legal counsel to monitor and report on legislative and regulatory developments related to explainability, fairness, and other ethics principles across North American and European jurisdictions.
• Collaborating with technology teams to identify, develop, and scale best practices, tools, and techniques for ethical data and AI use, including interpretability, explainability, and bias mitigation.
• Advising data and model stewards and stakeholders on techniques, tools, and latest developments around explainability and fairness, including guidance on trade-offs.
• Ensuring data and AI ethics policies and standards are inclusive of current requirements, and drafting new policies as needed.
• Supporting and promoting the adoption of data and AI ethics and governance practices across the organization by developing strategies and success metrics.
• Contributing to thought leadership and educational resources within and outside the organization.
• Participating in the creation, management, and analysis of data and AI governance policies and standards, including assessing potential impacts of policy decisions.

Requirements

• Strong familiarity with developments and trends in ethical data and trustworthy AI, including major global organizations like EU and UN.
• Understanding of data and model governance activities, oversight mechanisms, documentation, and development processes.
• Expertise and emerging leadership in ethics domains such as explainability and fairness.
• Knowledge of global data and AI privacy principles and regulations, with experience in GDPR and Canadian Privacy Act considered an advantage.
• Deep technical knowledge in data management, data governance, and data quality, including experience with tools like Cloud, Data Lake, SQL, Python, Alteryx.
• Solutions-oriented critical thinking skills with strong influencing and networking abilities.
• Ability to translate technical and business issues into actionable plans and deliver results independently.
• 4-6 years of academic or industry experience in data management and responsible AI.
• Higher education and certifications in data management, machine learning, AI, or technology ethics are considered a strong asset.

Nice to Have

• Experience working with data management, ModelOps, and traditional software development life cycles.

Qualifications

• 4-6 years of academic or industry experience in data management and responsible AI.
• Masters degree or higher in relevant fields is a considered a strong asset.
• Certifications in data management, machine learning, AI, or technology ethics are advantageous.

Benefits & Perks

• Hybrid Work Model with flexible in-office and remote days.
• Flexibility & Work-Life Balance policies including work from anywhere for up to 8 weeks per year.
• Career Development and Growth programs focused on continuous learning and skill development.
• Comprehensive benefits including flexible vacation, mental health days, retirement savings, tuition reimbursement, incentive programs, and wellbeing resources.
• Inclusive and flexible company culture emphasizing values like customer obsession, winning, challenging thinking, acting fast, and collaboration.
• Social Impact initiatives including paid volunteer days and opportunities for community involvement.
• Competitive US benefits including health, dental, vision, disability, life insurance, 401k with match, paid time off, parental leave, sabbatical, and additional insurance options.