Director-Data Science
Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. WNS scores A on the Alion truth index.
WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence - WNS’ core differentiator - with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.
Role OverviewWe are seeking an experienced Director to lead AI/ML, Generative AI and Data Science engagements across multiple clients. The role requires strong delivery leadership, solution architecture, technical expertise, client management and people leadership to drive scalable AI solutions and business outcomes.Key ResponsibilitiesDelivery LeadershipLead multiple AI/ML, Data Science and GenAI engagements, ensuring quality, timelines, resource utilization and business outcomes. Establish delivery governance, engineering standards and best practices. Drive solutions from proof of concept to production while managing risks, escalations and delivery challenges.Solutioning & Technical LeadershipLead solution architecture and technical solutioning for AI/ML, GenAI and advanced analytics opportunities. Translate business challenges into scalable, commercially viable solutions. Drive technical discussions, project scoping, effort estimation and client presentations. Provide architectural direction and evaluate emerging technologies and platforms.Client & Stakeholder ManagementBuild relationships with senior client stakeholders and own engagement governance, communication and executive reviews. Act as the primary interface between clients, internal leadership and delivery teams. Manage expectations, resolve escalations and identify opportunities for account growth.People & Practice ManagementLead and mentor Data Scientists, ML Engineers, AI Engineers, GenAI specialists and technical leads. Drive performance management, career development, succession planning, talent retention and capability building. Oversee resource planning and develop second-line leaders while fostering accountability, innovation and continuous learning.Business Growth & ConsultingPartner with sales, consulting and account leadership to identify AI/ML/GenAI opportunities. Support pre-sales, RFP/RFI responses, proposals, solution presentations and client workshops. Drive account expansion, reusable accelerators and intellectual property while demonstrating business value and ROI.Technical Skills & CompetenciesStrong Python proficiency and expertise in AI/ML engineering, Data Science, statistics, predictive modelling and advanced analytics. Deep understanding of machine learning, model lifecycle management, deployment, monitoring and MLOps. Hands-on exposure to Generative AI, LLMs, RAG, agentic AI, prompt engineering, vector databases and enterprise GenAI applications. Familiarity with Scikit-learn, TensorFlow, PyTorch, LangChain, Hugging Face and cloud platforms such as Azure, AWS or GCP. Ability to guide architecture and evaluate scalable technical solutions.Experience & Qualifications14+ years of experience in Data Science, AI/ML, AI Engineering, Advanced Analytics or technology consulting. Proven track record of managing multiple AI/ML/GenAI engagements, large technical teams, senior client relationships, solution architecture and pre-sales activities. Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics or a related discipline.Leadership CompetenciesExcellent communication, presentation, stakeholder management, influencing and negotiation skills. Strong problem-solving, strategic thinking, decision-making and execution capabilities. Demonstrated ownership, people leadership, mentoring, coaching and conflict resolution.Measures of SuccessSuccessful delivery of AI/ML/GenAI engagements, high client satisfaction, conversion of solutioning opportunities into projects, improved delivery efficiency and technical quality, development of strong technical leaders, and sustainable portfolio growth through innovation and account expansion.
Graduate or above