Job Description

About the Role

Are you a data science innovator passionate about ensuring AI operates responsibly and ethically? Do you dream of pioneering solutions that balance technological innovation with societal impact? As a Sr. Data Scientist specializing in AI Governance, you’ll drive cutting-edge initiatives to shape how AI systems are designed, monitored, and governed.

This role is your chance to combine your technical expertise with strategic oversight, ensuring AI models are fair, transparent, and aligned with global standards. You’ll join a forward-thinking team committed to embedding trust into AI and unlocking its full potential responsibly.

What You'll Do

• Innovate AI Frameworks: Develop scalable models and algorithms that integrate fairness, accountability, and transparency into AI solutions.
• Governance Strategies: Design and implement robust mechanisms to monitor AI compliance with ethical standards and regulations.
• Risk Management: Identify, analyze, and mitigate potential biases or risks in AI/ML models, ensuring integrity across projects.
• Collaborate Across Teams: Partner with engineers, legal experts, and policymakers to drive AI governance initiatives.
• Data-Driven Insights: Leverage large datasets to inform decision-making, enhance model performance, and ensure data privacy standards are upheld.
• Thought Leadership: Stay ahead of industry trends, publishing findings and representing the company at global AI ethics forums.

What You Bring

• Experience: 5+ years in data science, AI/ML, or a related field, with a focus on governance or ethical AI.
• Technical Mastery: Proficiency in Python, R, or similar languages, with a strong foundation in statistical modeling and machine learning frameworks.
• Domain Knowledge: Familiarity with AI ethics, governance frameworks (e.g., EU AI Act, NIST AI RMF), and data privacy regulations.
• Analytical Mindset: Ability to break down complex problems and deliver actionable insights.
• Communication Skills: Adept at explaining technical concepts to non-technical stakeholders and drafting comprehensive reports.
• Leadership: A proactive mindset with the ability to lead cross-functional teams and mentor junior data scientists.