Company Description
WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees.
Job Description
- Analytics Function Overview The Analytics function enables next-generation Business Intelligence through AI-driven insights, self-service analytics, and conversational reporting for global pharmaceutical organizations.
- It partners with Commercial, Medical, Market Access, and Executive stakeholders to scale insight delivery and reduce manual reporting.
- The AI & Self-Service Analytics team operationalizes AI-assisted analytics, natural language data interaction, and persona-based self-service datasets across enterprise BI and cloud data platforms.
Roles And Responsibilities
- Summary Design and deliver AI-enabled reporting and self-service analytics aligned to pharma commercial and medical use cases.
- Support conversational BI capabilities and translate business questions into AI-assisted workflows such as variance analysis, trend detection, and anomaly identification. Build persona-based self-service datasets for analysts, data scientists, and business users.
- Collaborate with BI and semantic layer teams to ensure AI readiness of data products including metadata and KPI logic. Configure and validate natural language query patterns mapped to governed KPIs. Develop automated KPI narratives and insight explanations.
- Identify high-value AI reporting use cases including field performance insights, payer mix analysis, and launch indicators. Support UX design for AI interactions including prompt design and explainability views.
- Ensure AI outputs remain transparent, auditable, and compliant with governance standards. Contribute to training and adoption materials and support program milestones under leadership guidance.
Core Competencies Technical Skills
- Experience with Power BI including Copilot features and semantic models. Experience with Tableau including Pulse and guided analytics. Strong SQL skills for data validation and analytics readiness.
- Understanding of semantic layers, KPI governance, and structured datasets. Exposure to cloud data platforms such as Snowflake or Databricks.
- Familiarity with LLM concepts, prompt design, embeddings, and AI explainability principles.Domain & Functional KnowledgeWorking knowledge of pharma commercial analytics including sales performance, field effectiveness, market access, and omnichannel analytics.
- Understanding of pharma datasets including CRM activity, sales, claims, payer, and digital engagement data. Ability to translate business questions into AI-driven analytics patterns.
- Behavioral & Professional Skills
- Strong stakeholder communication skills with structured analytical thinking.
- Ability to collaborate with global cross-functional teams including business, IT, and governance teams.
- Strong attention to detail and quality-focused mindset. Adaptability to evolving AI and analytics technologies with a collaborative team-oriented approach.
Must-Have Skills
- Experience with Power BI Copilot or Tableau Pulse. Strong SQL and data validation capability. Strong documentation and communication skills.
- Experience supporting self-service analytics or advanced BI users.
- Understanding of KPI-driven reporting and semantic data models. Strong structured problem-solving ability.
Good-to-Have Skills
- Exposure to conversational analytics or NLP-based querying. Experience with AI insight generation or explainability features.
- Knowledge of pharma therapy areas or launch analytics. Familiarity with Databricks, Python, or AI notebooks. Experience supporting global or multi-region BI programs.
Qualifications
Bachelor's or Master's degree in Engineering, Computer Science, Data Analytics, Statistics, or related quantitative fieldStrong academic background with exposure to analytics, data, or AI coursework
