Description
Ness is a full lifecycle digital engineering firm offering digital advisory through scaled engineering services. Combining our core competence in engineering with the latest in digital strategy and technology, we seamlessly manage Digital Transformation journeys from strategy through execution to help businesses thrive in the digital economy. As your tech partner, we help engineer your company's future with cloud and data. For more information, visit www.ness.com We are problem-solvers, architects, strategists, implementors, and lifelong learners. We collaborate with each other and with our clients to help them meet their short- and long-term technology goals. Our culture is open, transparent, challenging, and fun. We hire smart, self-starters who thrive in an open-ended environment to figure out what needs to be done and take ownership in delivering quality results Job Title: Manager, Data & AI Compliance Role Description: The Manager, Data & AI Compliance is a critical leadership role responsible for ensuring all data practices and AI activities within the organization comply with both internal policies and external regulations. This involves continuous monitoring of compliance status, conducting thorough adherence checks, and managing issue resolution processes related to non-compliance incidents. The Manager will be instrumental in developing comprehensive compliance policies that are in line with industry standards and regulatory requirements. This position requires close collaboration with privacy, compliance, risk, and legal teams to stay current on changes in laws and regulations affecting the organization's operations.The Manager will perform regular assessments to identify potential areas of non-compliance and propose corrective actions to mitigate associated risks. Additionally, this role includes creating and implementing awareness programs designed to educate employees on the importance of adhering to governance guidelines. The Manager will prepare detailed reports that highlight key findings from audits and suggest improvements where necessary. They are also responsible for maintaining up-to-date documentation of all compliance-related activities to ensure transparency and accountability. In cases of non-compliance, the Manager plays a crucial role in resolving issues by working collaboratively with relevant departments to address root causes and prevent recurrence. Key Responsibilities: Policy Development:- Create Comprehensive Policies: Develop comprehensive compliance policies for data handling and AI usage that align with industry standards and regulatory requirements.
- Collaboration: Regularly review and update these policies in collaboration with legal, IT, privacy, risk management, and other business units.
- Framework Establishment: Establish a clear framework for policy implementation across the organization.
- Compliance Audits: Conduct regular audits to assess compliance with established policies.
- Risk Identification: Identify potential risks or areas for improvement through detailed analysis.
- Corrective Actions: Ensure that corrective actions are implemented promptly based on audit findings.
- Continuous Improvement: Use insights gained from audits to refine and enhance compliance strategies continuously.
- Manage Incidents: Oversee the resolution process for non-compliance incidents by coordinating with relevant departments.
- Root Cause Analysis: Conduct root cause analysis to understand underlying issues leading to non-compliance.
- Preventive Measures: Implement preventive measures to avoid recurrence of similar issues.
- Detailed Reports: Prepare detailed reports on compliance status for senior management.
- Highlight Findings: Highlight key findings from audits and recommend actionable corrective measures.
- Provide Insights: Ensure that reports are clear, actionable, and provide valuable insights into the overall compliance health of the organization.
- Identify Risks: Conduct thorough risk assessments to identify potential areas of non-compliance within data handling and AI activities.
- Mitigation Plans: Collaborate with stakeholders to develop effective mitigation plans addressing identified risks.
- Monitor Effectiveness: Monitor the effectiveness of mitigation plans and make adjustments as necessary.
- Maintain Records: Maintain up-to-date documentation of all compliance-related activities, including policies, procedures, audit results, training materials, and more.
- Accessibility: Ensure documentation is easily accessible to relevant stakeholders.
- Regular Review: Regularly review documentation for accuracy and relevance.
- Work Together: Work collaboratively with IT, legal, HR, privacy, risk management, and other business units to ensure cohesive implementation of compliance initiatives across the organization.
- Shared Responsibility: Foster a culture of shared responsibility for compliance by engaging stakeholders at all levels.
- Stay Updated: Stay informed about changes in laws and regulations affecting data handling and AI practices.
- Policy Updates: Update internal policies accordingly in response to regulatory changes.
- Communication: Communicate changes promptly to relevant stakeholders to ensure ongoing compliance.
- Bachelor's degree in Information Technology, Business Administration, Law, or a related field (Master's degree preferred).
- Proven experience in a compliance or risk management role, preferably within the data or AI sectors.
- Strong understanding of data privacy laws (e.g., GDPR, CCPA) and AI ethics guidelines.
- Excellent analytical skills with the ability to interpret complex regulations effectively.
- Exceptional communication skills, both written and verbal.
- Strong project management abilities with keen attention to detail.
- Ability to work collaboratively across various departments within the organization.
- Certifications such as Certified Information Systems Auditor (CISA), Certified Information Privacy Professional (CIPP), or similar credentials.
- Experience using compliance management tools and software.
- Understanding emerging trends in AI technology and their regulatory implications.