Role Summary
The Senior AI Consultant will leverage over 10 years of consulting experience and deep expertise in Artificial Intelligence and Machine Learning to drive significant business transformation for clients. This role involves assessing client needs, developing robust AI strategies, overseeing the implementation of cutting-edge AI solutions, and ensuring ethical and responsible AI governance.
Key Responsibilities
- Strategy & Vision: Evaluate clients' business needs, existing data infrastructure, and operational challenges to define and articulate a comprehensive, value-driven AI strategy and roadmap.
- Solution Design & Implementation: Design, architect, and oversee the end-to-end development and deployment of scalable AI/ML solutions (e.g., NLP, computer vision, generative AI, predictive models).
- Client Management & Stakeholder Collaboration: Act as the primary liaison with executive-level stakeholders, conveying complex technical concepts to non-technical audiences and securing buy-in for AI initiatives.
- Project Leadership & Delivery: Lead cross-functional project teams, including data scientists, data engineers, and software developers, ensuring timely, budget-conscious, and high-quality solution delivery using agile methodologies.
- Ethical AI & Governance: Develop and enforce policies for responsible AI usage, ensuring solutions comply with regulatorystandards (e.g., GDPR, HIPAA) and adhere to principles of fairness, transparency, and data privacy.
- Adoption & Training: Drive organizational change management, developing training programs and internal capabilities to ensure clients can effectively utilize and maintain the deployed AI solutions.
Requirements (Minimum Qualifications) 📜
- Experience: Minimum of 10 years of experience in a technology or management consulting role, with a significant focus (at least 5 years) on AI, Machine Learning, or Advanced Analytics.
- Technical Expertise: Proven knowledge of machine learning and data science theory, techniques, and tools.
- Platform Knowledge: Strong understanding of cloud-based AI platforms (e.g., AWS SageMaker, Azure AI, Google Cloud AI Platform) and big data technologies.
- Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field.