Job Description
Associate Director - Customer Behavior Analytics, Customer Knowledge & Measurement
Job Description :
This role sits within the Customer Knowledge & Measurement (CK&M) vertical of Digital Human Health (DHH). The Associate Director, Customer Behavior Analytics owns the "know the customer" of CK&M: the model-build and insight-generation layer that produces the customer understanding the rest of CK&M (Field & CRM Engagement) acts on and measures.
The Associate Director will be responsible for leading the analytics that define who matters and why: HCP / account / consumer segmentation, micro segmentation, propensity and risk-stratification modelling, integrated customer profiling, KOL identification, content-affinity modelling, campaign analytics and the data-product spine that powers downstream activation. The team supports US Commercial Organisation - informing customer engagement strategy.
The role is a key node in evolving the India Hub from delivery support to strategic analytics partner across the customer-insight value chain.
Role Overview :
The Associate Director will lead a team of 15+ covering capability domains under Customer Behavior Analytics. The candidate must be able to lead direct teams and orchestrate cross-functional insights pods spanning DHH, Data Strategy & Solutions, IT and the broader DHH organisation. The individual will demonstrate consistently strong leadership, the ability to work objectively in ambiguity, strong partnership skills, and a culture of continual learning.
The preferred candidate will have an entrepreneurial spirit, a consultative and strategic mindset, deep customer-analytics experience in pharma / biotech (segmentation, micro-segmentation, campaign analytics, productised customer-data offerings), fluency in technology (AI, agentic, GenAI), and a demonstrated record of producing actionable insights from analytics. The individual should have a strong understanding of the US data landscape - claims, EMR / EHR, Rx, activity, promotional data, content-engagement data — and the ability to translate ambiguous business questions into advanced, scalable analytical solutions.
Key Responsibilities :
- Customer model-build: Lead the development of customer-understanding models that drive downstream activation and measurement — HCP segmentation (personal / non-personal), account / IDN segmentation, patient segmentation and profiling, propensity models (writer / non-writer), patient risk-stratification (initial model build with analog / business-rules and progressing to ML), and early adopter / follower analysis.
- Integrated Customer Profile (ICP) and KOL build: Own the analytics build for ICP and the KOL-identification capability (KOLeidoscope build). Define data inputs, model logic, refresh cadence and validation criteria.
- Patient Insights Engine (PIE) and consumer extensions: Lead the build and evolution of the customer-data spine across PIE phases - CDM, Business Rules, Data Augmentation (incl. EMR), and Predictive Models — and the consumer extension (PIECON) where applicable.
- Content Affinity: Drive micro-segmentation analytics to enable targeted content recommendations and quantify which content resonates with distinct segments, informing both brand strategy and Field & CRM execution.
- Team leadership and cross-functional orchestration: Lead and mentor Senior Managers (and the specialists / interns reporting into them), providing guidance on best practices in data analytics, modelling, validation and insight synthesis. Manage team workload proactively and ensure optimal resource utilisation. Lead cross-functional insights pods in addition to direct teams.
- Prioritisation and value tracking: Understand the full book of work underway and planned for each disease area or business unit. Work with BU LT to prioritise against team’s capacity. For prioritised work, engage cross-functional teams to articulate the value and impact of each piece. Encourage the mindset to articulate the "so what" and "now what" and to track realised business value.
- Stakeholder collaboration: Drive proactive, transparent engagement with cross-functional partners to co-create solutions, align on organizational priorities, and set clear expectations. Provide internal and business stakeholders with forward-looking visibility into key programs to inform milestones, prioritization, risk mitigation, and aligned decision-making.
- Pharma data-ecosystem analytics: Analyse data across disparate data sources (claims, EMR, Rx, activity, promotional, consumer, content) to develop insights that inform commercial business strategies.
- Leverage advanced statistical methods and ML/AI modeling with strong validation practices; deliver regression and time-series models, and segmentation/clustering approaches (k-means, hierarchical) to generate actionable insights.
- Innovation and GenAI experimentation: Contribute to and lead innovation experiments - idea generation, idea incubation, experimentation - including responsible application of GenAI, agentic AI. Identify tangible, measurable criteria to make meaningful improvements to business processes.
Education Requirements :
Masters (or equivalent) in Data Science, Mathematics, Computer Science, Statistics, Decision Science, Marketing, Engineering, Management or an equivalent commercial discipline. Advanced degree (MBA, MS, PharmD, PhD) is preferred
Required Experience and Skills :
- 8+ years in pharma/biotech across commercial analytics, strategy with deep pharmaceutical commercialization experience, and delivery of complex analytical initiatives.
- 4+ years leading high-performing teams; proven ability to coach talent, build inclusive culture, and lead cross-functional pods in a matrixed setup.
- Strong consultative mindset with demonstrated ability to translate brand and commercial strategies into actionable analytics and insight plans.
- Executive presence with ability to influence senior leaders, align US Marketing & DHH stakeholders, and communicate clear, data-driven narratives.
- Extensive experience working with real-world datasets (claims, Rx, CRM, promotional and sales data), leveraging SQL, Python, and AI-driven tools; familiarity with modern data platforms including Snowflake, Databricks, and AWS/GCP
- Experience leveraging advanced statistical methods, Machine Learning / AI and Natural Language Processing (NLP) modelling and model evaluation. Segmentation & clustering (k-means, hierarchical).
- Self-motivated, proactive mindset, and ability to work independently.
Required Skills:
Business Analysis, Business Processes, Business Process Improvements, Customer Engagement, Data Analytics, Data Science, Demand Management, Digital Healthcare, Innovation, Machine Learning (ML), Pharmacodynamics, Pharmacology, Propensity Models, Requirements Management, Sourcing and Procurement, Stakeholder Relationship Management, Strategic Planning, Team Leadership, US Marketing, Value Chain
Preferred Skills:
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**Employee Status: **
Regular
Relocation:
Domestic
VISA Sponsorship:
No
Travel Requirements:
10%
Flexible Work Arrangements:
Hybrid
Shift:
Not Indicated
Valid Driving License:
No
Hazardous Material(s):
NA
Job Posting End Date:
07/31/2026
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