Leads executive client engagements and large analytics, data, AI, and digital transformation programs, primarily for manufacturing and automotive organizations. Responsibilities include strategy development, solution design, consulting, proposal leadership, account growth, commercial management, delivery oversight, governance, team mentorship, and capability building. The role connects business priorities with data platforms, AI solutions, operational improvements, and measurable financial outcomes.
Key Responsibilities
Client Leadership & Executive Engagement
- Build trusted relationships with client executives and senior business, data, digital, operations, engineering, supply chain, and technology leaders.
- Independently lead steering committees, quarterly business reviews, transformation workshops, roadmap discussions, and executive working sessions.
- Translate business priorities and operational challenges into analytics, data, AI, and digital transformation initiatives.
- Present complex findings, recommendations, and investment cases through clear executive storytelling and data-driven narratives.
- Act as the primary client-facing leader for strategic engagements and maintain alignment across client and EXL leadership teams.
Manufacturing & Automotive Transformation
- Lead analytics and AI programs across manufacturing operations, supply chain, procurement, logistics, production planning, demand planning, and inventory optimization.
- Shape solutions for quality analytics, warranty analytics, connected manufacturing, engineering analytics, plant performance, digital manufacturing, and industrial AI.
- Identify high-value use cases supporting throughput, productivity, quality, cost, service, working capital, asset performance, safety, and sustainability outcomes.
- Connect business priorities with practical operating-model, process, data, analytics, and technology interventions.
Data & AI Transformation
- Define enterprise analytics and AI strategies, transformation roadmaps, and prioritized use-case portfolios.
- Lead data-platform modernization, cloud migration, data engineering, data management, governance, quality, integration, and analytics enablement initiatives.
- Guide solutions across descriptive, predictive, prescriptive, optimization, simulation, forecasting, root-cause analysis, and operational intelligence use cases.
- Enable machine learning, generative AI, agentic AI, and decision-intelligence solutions through scalable and governed data foundations.
- Partner with architects, engineers, data scientists, and business teams to ensure solutions are secure, scalable, adoptable, and tied to measurable outcomes.
Solutioning & Business Development
- Lead solution design and consulting engagements for both focused initiatives and complex multi-workstream transformation programs.
- Own or contribute to proposals, RFPs, RFIs, statements of work, executive pitches, and deal-shaping discussions.
- Develop transformation roadmaps, delivery approaches, staffing models, workplans, effort estimates, cost estimates, assumptions, dependencies, and risks.
- Present differentiated solutions to executive stakeholders and guide opportunities from qualification through closure and transition to delivery.
- Collaborate with sales, account, industry, capability, architecture, and delivery leaders to expand strategic client relationships.
Account Growth & Commercial Leadership
- Provide independent leadership for client portfolios and engagements valued up to $10M-$15M annually.
- Develop account growth strategies and identify cross-sell and upsell opportunities across analytics, data, AI, GenAI, and transformation services.
- Build executive relationships across multiple client functions and create a forward-looking opportunity pipeline.
- Apply strong financial and commercial discipline to scope, pricing, margins, staffing, utilization, and delivery commitments.
Delivery Leadership
- Provide executive oversight across multiple programs and workstreams from discovery through implementation and managed delivery.
- Establish program governance, monitor risks and dependencies, and drive timely resolution of delivery and stakeholder issues.
- Ensure high-quality outcomes, strong customer satisfaction, effective resource planning, and disciplined performance management.
- Mentor delivery managers, engagement leads, solution architects, analytics leaders, and technical teams.
Capability Building & Innovation
- Build and scale Manufacturing Analytics, Data, AI, and GenAI capabilities, solutions, and reusable assets.
- Develop industry-specific frameworks, maturity assessments, accelerators, reference architectures, case studies, and points of view.
- Contribute to hiring, team building, talent development, competency planning, and communities of practice.
- Drive thought leadership and innovation across smart manufacturing, connected operations, digital thread, digital twins, industrial data, and AI-enabled decision-making.
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Required Experience & Qualifications
- 12-18 years of experience across analytics, data, AI, digital transformation, management consulting, or technology-enabled business transformation.
- At least five years of client-facing leadership experience across analytics, data, AI, or transformation engagements.
- Proven ability to independently manage strategic client relationships and portfolios or engagements valued up to $10M-$15M annually.
- Experience leading executive discussions, steering committees, transformation workshops, roadmap development, and solution presentations.
- Demonstrated ability to create compelling executive stories that connect data and analytical insights to business priorities and financial outcomes.
- Strong understanding of the end-to-end data and AI lifecycle, including data engineering, data management, cloud data platforms, business intelligence, advanced analytics, machine learning, generative AI, deployment, governance, and adoption.
- Experience leading proposals, RFPs, solution architecture, staffing, effort estimation, cost estimation, commercial inputs, and transition planning.
- Ability to lead multidisciplinary teams across business consulting, data engineering, analytics, AI, architecture, program management, and change enablement.
- Bachelor’s or master’s degree in engineering, computer science, data, analytics, operations, business, or a related discipline.
Industry Experience
- Preferred experience in Manufacturing Analytics, Automotive, Mobility, Industrial Manufacturing, Heavy Equipment, Industrial Products, Aerospace, Transportation, or related manufacturing-intensive sectors.
- Automotive OEM, Tier 1 supplier, connected vehicle, manufacturing engineering, plant operations, supply chain, quality, warranty, or aftersales experience is highly desirable.
- Experience working with large, complex global manufacturers or industrial enterprises with distributed plants, functions, and technology environments.
Preferred Qualifications
- Experience supporting organizations such as automotive OEMs, automotive suppliers, industrial manufacturers, equipment manufacturers, or engineering-intensive enterprises.
- Experience with Azure, AWS, GCP, Databricks, Snowflake, Microsoft Fabric, Power BI, Tableau, or comparable data and analytics ecosystems.
- Exposure to smart manufacturing, Industry 4.0, connected factory, digital thread, digital twins, predictive maintenance, industrial IoT, and manufacturing execution environments.
- Experience shaping or leading GenAI use cases in engineering, manufacturing, supply chain, quality, warranty, service, knowledge management, or commercial operations.
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- Experience building an industry offering, center of excellence, reusable assets, strategic partnerships, or high-performing multidisciplinary teams.
Leadership Competencies
- Executive presence and trusted-advisor mindset
- Consultative selling and commercial orientation
- Executive storytelling, influence, and presentation capability
- Manufacturing and operational business acumen
- Strategic thinking with strong execution discipline
- Financial acumen and account-growth mindset
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