# Lead Data Scientist - AI Delivery at Wolters Kluwer

Wolters Kluwer is hiring a Lead Data Scientist - AI Delivery in Pune, India. Level rates it Builds AI ●●●●; you can [apply on Wolters Kluwer](https://jobsbylevel.com/go/0d697cbe-48a7-4b69-a756-22c8b8c862be?utm_medium=ai-agent).

AI Level 4, AI centrality 90 out of 100. IND-Pune-Smartworks.

## Details

- Company: [Wolters Kluwer](https://jobsbylevel.com/companies/wolters-kluwer)
- AI level: AI Level 4 (score 90 out of 100)
- Location: IND-Pune-Smartworks
- Posted: October 28, 2026
- Apply: https://jobsbylevel.com/go/0d697cbe-48a7-4b69-a756-22c8b8c862be?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=lead-data-scientist-ai-delivery-at-wolters-kluwer-8583e5

## Prepare for this job

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## Description

About the Role The FCC DnA team is seeking an experienced Lead Data Scientist to provide technical and delivery leadership across multiple AI and Data Science initiatives. This role will serve as a key India delivery partner to the U.S. AI leadership team and will be responsible for independently driving execution across products and use cases such as Data Integrity, intelligent document processing, Broker Statement processing, workflow automation and other Applied AI initiatives. The role requires a strong technical leader who can manage a small team, translate business priorities into executable plans, remove delivery blockers and work effectively across Data Science, Product, Engineering and Platform teams. Since these solutions are deployed on the Digital Twin platform, the successful candidate should be comfortable working with platform engineering teams on APIs, environments, deployments, integrations, monitoring and production issues. This is not intended to be a pure people-management role or a pure modeling role. The person should maintain strong technical depth across Data Science, Machine Learning and Applied AI, while also understanding enough software and platform engineering to move solutions from development through production. Experience with Statistical Modeling and model lifecycle management is a strong plus, as the role will also support and collaborate with the broader AI Modeling team. The successful candidate should be able to work independently with limited day-to-day supervision, take ownership of delivery outcomes, communicate risks and decisions clearly, and present technical progress and recommendations confidently to senior leaders. Key Responsibilities · Own end-to-end delivery of multiple AI and Data Science initiatives from requirements and solution design through development, testing, deployment and production stabilization. · Act as the primary India delivery lead for assigned initiatives and independently manage priorities, milestones, dependencies, risks and execution. · Lead and mentor a small team of Data Scientists, AI Engineers and technical resources, providing clear direction, technical guidance and accountability. · Translate ambiguous business problems into practical AI, analytics and engineering solutions aligned to business outcomes. · Partner closely with the Digital Twin platform team to resolve environment, integration, deployment, performance and production issues. · Provide sufficient technical depth to distinguish whether issues originate in the model, application, integration, data or platform layer and coordinate the appropriate resolution. · Participate in solution architecture and design discussions and ensure solutions are scalable, reliable, secure and maintainable. · Guide teams on API integrations, data pipelines, authentication, cloud environments, CI/CD, logging, monitoring and other production dependencies. · Provide technical oversight for Machine Learning, NLP, document intelligence, Generative AI, RAG and Agentic AI solutions. · Review model and AI approaches, evaluation methodology, error analysis, performance metrics and implementation trade-offs. · Partner with the AI Modeling team on model development, validation, monitoring, drift detection and productionization when required. · Drive root-cause analysis and corrective actions when solution accuracy, reliability or production performance is below expectations. · Promote reusable frameworks, components and delivery patterns that can support multiple products and customers. · Partner with Product, Business, Advisory, Engineering and Content teams to ensure technical delivery remains aligned to customer and business needs. · Provide concise status updates covering progress, risks, dependencies and decisions required, and escalate issues early with recommended actions. · Present technical solutions, delivery updates and recommendations clearly to senior leaders and non-technical stakeholders. · Support hiring,

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