Associate Director, US Market Engagement Data Science & Advanced Analytics

This role will reside within the DHH US Market Engagement Team for Pharma. This team provided strategic thought-partnership to US commercial stakeholders through understanding brand strategy, co-creating DHH demand and associated business requirements aligned to business priorities. The US Market Engagement team Quarterbacks demand fulfillment and leads the activation of DHH products and services. The Associate Director, US Market Engagement, Data Science & Advanced Analytics, will be responsible for developing data-driven insights to inform brand strategy and tactics in support of the pharma portfolio.

This role will focus on applying advanced data science to deliver strategic non-product DHH services to US Pharma Business unit such as HCP targeting/segmentation, call planning, campaign measurement & effectiveness etc.

• Translate business needs and priorities to build analytical plans that answer business questions by providing actionable insights. Effectively communicating advanced analytics to stakeholders to inform business decisions.
• Communicate & collaborate effectively with cross functional teams with competencies in market research, forecasting, commercial analytics, data science, customer engagement, data strategy, population health, competitive insights, marketing operations, medical & clinical backgrounds.
• Analyze data across disparate databases/sources (including claims/EMR, DDD, and other sources) to develop insights that inform commercial business strategies.
• Stay current with industry trends and advancements in analytical methodologies to bring new ideas forward (including application of GenAI) that will enhance analytic capabilities of the organization.
• Contribute to innovative experiments, specifically to idea generation, idea incubation and/or experimentation, identifying tangible and measurable criteria to make meaningful improvements to the business processes and strategies.
• Derive actionable business insights from various data sources, develop clear data story, and communicate effectively to business stakeholders.
• Lead and mentor a team of data scientists and business analysts (on-shore and off-shore), providing guidance on best practices in data analytics, modeling and data visualization, through the scope of a project.

• BS (or equivalent) in Data Science, Mathematics, Economics, Computer Science, Statistics, Decision Science, Marketing, Engineering, or Public Health is required.
• MBA, MS or PhD degree is preferred

• 5+ years of relevant experience delivering complex analytical projects in the pharmaceutical, biotech, consulting, or healthcare industry.
• Knowledge in mining patient medical claims/EMR data as well as other healthcare datasets with a strategic mindset and proven record of being able to produce actionable business insights that drive positive commercial results.
• Self- motivated, proactive mindset, and ability to work independently.
• Story-telling and executive presence with senior leaders.
• Effective interpersonal skills, communication skills, and stakeholder management, including experience collaborating in a matrixed organization and ability to align stakeholders on data-driven decisions.
• Strong business acumen and consultative skills, with proven ability to comprehend pharmaceutical business processes and commercial strategies in detail and translate these into detailed business standards/questions that power analytics.
• Effective organizational and project management skills to work effectively across the organization and manage a team of business analysts and data scientists efficiently and effectively.
• Innovative thinking with affinity toward experimentation and appropriate risk-taking, including curiosity about how agentic AI and automation can enhance commercial analytics and insight generation.
• Awareness of the opportunities, limitations, and responsible use of AI (including agentic AI) in a regulated environment (e.g., data privacy, validation of AI-generated outputs).
• Prior hands-on experience working with healthcare data especially EMR/EHR, Claims Data (i.e. IQVIA APLD) and various data offerings.
• Ability to develop efficient programming code and software assets that provide advanced analytical functionality.
• Proven data science experience leveraging advanced statistical methods, Machine Learning/ Artificial Intelligence, Natural Language Processing (NLP) modeling and model evaluation is a plus.
• Knowledge of both machine learning and descriptive algorithms/modeling using such languages as Python, R studio, SAS, SQL etc.
• Understands the business context, challenge, limitation, constraints and goals to effectively match the capability of the statistical and mathematical and M/L approaches to the business, scientific and operational challenge.
• Travel may be required

• Preferred:
  Prior hands-on experience working with healthcare data and leveraging advanced analytics and modeling techniques
• MBA, MS…