Inverto | Manager - Digital, Data & AI

About Inverto

Role overview

Responsibilities

• Lead end-to-end data and AI engagements, including analytics, data transformation, predictive modeling, automation, and GenAI applications.
• Lead senior client meetings, steering committees, and workshops; translate complex topics into actionable recommendations.
• Design analytical solutions such as pipelines, dashboards, predictive models, and AI-enabled tools; develop data-backed business cases.
• Develop new offerings, reusable assets, and scalable solutions using emerging technologies.
• Contribute expertise to proposals, pitches, opportunity assessments, and go-to-market narratives.
• Lead project teams, coach junior colleagues, and ensure high-quality delivery.
• Create and improve internal tools, code libraries, benchmarks, and best practices.
• Support recruitment, capability building, training, and practice growth.

Requirements

• 5–6+ years of data analytics, AI, or digital consulting experience, including client-facing project delivery.
• Bachelor’s degree in a relevant field; a Master’s degree is preferred.
• Experience leading client engagements and teams and driving data and analytics project outcomes.
• Strong data analysis, visualization, and transformation skills using tools such as SQL, Power BI, and Excel; hands-on Python expertise.
• Experience with cloud platforms and/or modern data ecosystems.
• Practical exposure to AI and GenAI technologies and their business applications.
• Ability to turn procurement and supply-chain business problems into scalable analytics and AI solutions.
• Strong communication and stakeholder management across technical and business audiences.
• Business-fluent written and spoken English.
• Willingness to travel to clients, potentially significantly depending on project needs.
• Independent, structured, accountable, results-oriented, collaborative, and entrepreneurial approach.

Relevant skills and domains

• Data analytics, AI, digital consulting, procurement, and supply chain.
• SQL, Power BI, Excel, Python, data transformation, and predictive modeling.
• Cloud platforms, modern data ecosystems, GenAI, LLMs, APIs, retrieval-based systems, and workflow orchestration tools.

Travel

• Client travel is required according to project needs and may be significant.