The Associate Director will lead the modernization of commercial performance analytics, transforming traditional reporting into AI-enabled, insight-driven decision support. The role is responsible for architecting and delivering enterprise-grade BI and analytics solutions using modern data platforms such as Databricks and cloud data warehouses, while driving advanced KPI harmonization and scalable semantic models.
This leader will spearhead GenAI-powered conversational analytics, intelligent automation, and agent-based insight generation to shift from reactive dashboards to proactive performance management. The role partners closely with commercial stakeholders to embed analytics into strategic decision-making and ensure executive-ready storytelling.
Additionally, the Associate Director will build and mentor high-performing analytics teams, champion data governance and compliance, and foster innovation across modern analytics, AI, and automation capabilities.
1. Commercial Performance Analytics Strategy
Define and execute the future-state vision for commercial performance analytics, evolving from static dashboards to AI-augmented, conversational, and proactive insights.
Partner with senior commercial leaders to embed analytics into performance reviews, planning cycles, and execution tracking.
Act as a thought leader for modern analytics platforms, advanced BI, and GenAI adoption within Commercial Reporting Analytics.
2. Advanced BI & Reporting Products
Lead the design and delivery of enterprise-grade reporting and analytics products, leveraging:
Power BI/Angular (enterprise semantic models, optimized DAX, deployment pipelines)
Standardized KPI frameworks and reusable metrics layers
Drive adoption of self-service analytics while maintaining strong governance, consistency, and performance.
Transition reporting from dashboard-centric delivery to insight-centric experiences, including narrative and AI-generated explanations.
3. Modern Analytics & Data Platform (Core Focus)
Architect and oversee analytics solutions built on modern platforms such as:
Databricks (Lakehouse architecture, Spark, Delta Lake)
Cloud data warehouses (Snowflake, BigQuery, Azure Synapse)
Lead analytics engineering best practices, including:
Advanced SQL and dimensional / semantic data modeling
Good to have experience of building data ingestion pipelines using Databricks, Dataiku, Airflow, and cloud-native orchestration tools
Partner with Data Engineering and IT to ensure:
Scalable, performant, and compliant data pipelines
Strong data quality, lineage, and governance controls
4. Advanced Performance Analytics & Insight Generation
Drive advanced analytical approaches focused on commercial performance, including:
Sales performance tracking and trend analysis
Forecast versus actual performance monitoring
Promotional and campaign performance measurement
Design scalable analytical frameworks that enable root-cause analysis, performance narratives, and actionable recommendations.
Translate complex analytical outputs into clear, executive-ready insights.
5. Generative AI & Conversational Analytics
Lead the design and deployment of GenAI-powered conversational analytics solutions, including:
Chatbots enabling natural-language interaction with commercial performance data
AI assistants delivering on-demand insights, explanations, and performance summaries
Implement enterprise-ready GenAI architectures using:
Azure OpenAI / OpenAI / Vertex AI
Retrieval-Augmented Generation (RAG)
Secure prompt engineering, evaluation, and monitoring frameworks
Ensure AI solutions adhere to pharma compliance, data privacy, and responsible AI standards.
6. Agent-Based Analytics & Intelligent Automation (Advanced / Emerging)
Design and pilot agent-driven analytics capabilities that:
Monitor KPIs and detect performance anomalies
Proactively generate insight narratives and alerts
Automate recurring reporting and analytical workflows
Collaborate with platform teams to evolve from reactive reporting to proactive, agent-enabled insight delivery.
Evaluate emerging agent orchestration and workflow automation frameworks.
7. Stakeholder Engagement & Insight Storytelling
Deliver compelling, executive-level storytelling through:
Interactive BI experiences
AI-generated narratives
Strategic presentations and leadership reviews
Act as a trusted analytics advisor to senior commercial stakeholders.
Influence decisions by clearly communicating what happened, why it happened, and what actions to take.
8. Team Leadership & Capability Building
Lead, mentor, and develop analytics professionals across:
BI and analytics engineering
AI-enabled reporting and insight delivery
Build team capability in modern analytics platforms, GenAI usage, and insight storytelling.
Foster a culture of innovation, automation, and continuous improvement.
Bachelor’s degree in Engineering, Computer Science, Information Systems, Statistics, Economics, or related field
Master’s degree or MBA preferred
12+ years of experience in commercial performance and advanced analytics, reporting, GenAI
Strong preference for pharmaceutical or life sciences commercial experience
Proven experience leading enterprise analytics modernization initiatives
Advanced expertise in Power BI/Angular (enterprise semantic models, DAX optimization, capacity management)
Strong hands-on experience with SQL and analytics engineering
Deep experience with Databricks/Dataiku (Lakehouse architecture, Spark, Delta Lake)
Experience with orchestration tools (dbt, Airflow, cloud-native pipelines)
Strong understanding of commercial performance data domains (sales, marketing, field activity)
Solid data governance, security, and compliance mindset
Experience building GenAI-powered chatbots or conversational analytics solutions
Hands-on exposure to LLMs, RAG architectures, prompt engineering, and AI evaluation
Familiarity with agent-based or autonomous analytics concepts
Python experience for analytics automation and AI integration
Strong executive presence and stakeholder management skills
Ability to balance strategic vision with hands-on execution
Comfortable driving innovation in complex, regulated environments
Excellent communication and storytelling abilities
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting, and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together. https://www.novartis.com/about/roadmap/people-and-culture
Commitment to Diversity & Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse team’s representative of the patients and communities we serve.
Values and Behaviors: Demonstrates and upholds Novartis values and behaviors in all aspects of work and collaboration.
Location: Hyderabad NKC. Hybrid | 3 days a week in office is mandatory.
Agility, AI Agents, AI Platforms, airflow, Chatbots, Commercial Analytics, databricks, Databricks Platform, data hub, dbt Core, Digital Marketing, Generative AI, Generative AI Agents, Intelligent Automation (IA), OpenAI, orchestration, power bi, Python (Programming Language), Qlik Sense, snowflake, Snowflake GenAI, Sql (Structured Query Language)
