Inverto | Manager - Digital, Data & AI

About Inverto

Role overview

Responsibilities

• Lead end-to-end analytics and AI engagements, including data transformation, predictive modeling, automation, and GenAI workstreams.
• Lead senior client meetings, steering committees, and workshops; translate complex concepts into actionable recommendations.
• Design analytics solutions such as data pipelines, dashboards, predictive models, and AI-enabled tools; build data-backed business cases.
• Develop digital and AI offerings, reusable assets, scalable solutions, and procurement and supply chain use cases.
• Contribute to proposals, client pitches, opportunity assessments, and go-to-market narratives.
• Mentor junior colleagues, lead project teams, and ensure high-quality delivery.
• Build internal tools, code libraries, benchmarks, and best practices; support recruitment, training, and capability building.

Qualifications

• 5–6+ years of professional experience in data analytics, AI, or digital consulting, including client-facing project delivery.
• Bachelor’s degree in a relevant field such as data science, engineering, computer science, or economics; a master’s degree is preferred.
• Experience leading client engagements, managing teams, and driving data and analytics project outcomes.
• Experience with analysis, visualization, and transformation tools such as SQL, Power BI, or Excel, plus 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 develop scalable analytics and AI solutions for complex business problems, particularly in procurement and supply chain.
• Strong communication and stakeholder management skills; business-fluent written and spoken English.
• Entrepreneurial, collaborative, accountable consulting approach, with structured thinking and ability to influence stakeholders.
• Willingness to travel for client and project needs, sometimes significantly to client sites.

Relevant technologies and expertise

• Relevant experience includes data analytics, AI, digital consulting, Python, data analysis, visualization, and transformation.
• Examples of tools and technologies include SQL, Power BI, Excel, cloud platforms, modern data ecosystems, LLMs, APIs, retrieval-based systems, and workflow orchestration tools.

Client travel

• Travel depends on client needs and project nature; the role may require significant travel to client sites.

Team environment