.About the role Gartner's Consulting business is an extension of Gartner's industry-leading IT Research.
From CIOs to leaders in business and government, we help Gartner clients across enterprises translate insights into transformational actions and achieve their mission-critical priorities.
Leveraging the breadth of Gartner's resources, Consulting is growing rapidly, with unlimited potential to continue expanding our client base.
Technology Strategy Consulting: We help the C-suite make the right decisions based on how technology can transform their businesses.
In today's world, a consulting firm that is 'born digital' (with the ability to directly leverage the full power of Gartner's research and insights) has relevance to the most important strategic decisions any business will make.
We deliver value to clients in areas such as: IT Strategy Consulting Benchmarking Analytics and Optimization Typically, this helps Gartner's clients execute on their strategic priorities across all sectors, including: Digital Growth and Transformation Applications, Infrastructure and Security Modernization Sourcing and Spend Optimization The Role: You will help our clients navigate the complex world of modern AI, data science, and analytics.
We'll look to you to provide our clients with a unique business perspective on how data science and analytics can transform and improve their entire organization – starting with key business issues they face.
This is a high growth, high visibility area with plenty of opportunities to enhance your skillset and build your career.
Key Responsibilities: Ability to lead and manage consulting engagements and diverse teams of experts and delivery associates.
Work with clients to identify the business potential of Artificial Intelligence (AI) and establish AI strategies, define and prioritize AI use cases, establish AI governance, and collaborate with client stakeholders to understand technical and business constraints.
Collaborate with clients to establish AI programs and processes for scaling delivery of AI solutions (e.G., MLOPs, ModelOps).
Align AI strategies and use cases to required data assets, identify strategies for acquiring data assets (including the potential value of synthetic data), and design data pipelines to support data science and AI projects.
Apply various Machine Learning (ML) and analytics techniques to develop classification and prediction models and leverage foundation models to develop generative AI capabilities; integrate client, domain (e.G., finance, sales) and industry knowledge into the solution.
Collaborate with cross-functional teams to identify business problems and design experiments to test hypotheses.
Present findings, insights, and recommendations to both technical and non-technical stakeholders in a clear and concise manner