Hybrid Associate Director, Data Science, Advanced Analytics

at MSD

• Job title: Associate Director, Data Science, Advanced Analytics
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $156,900 - $247,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Python, SQL
• Location requirements: Hybrid, Rahway, United States

About the role

• Associate Director in Data Science focusing on advanced analytics for the Pharma portfolio. Leading data-driven insights and collaboration across teams to inform brand strategies.

Responsibilities

• 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.

Requirements

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

Benefits

• medical, dental, vision healthcare and other insurance benefits (for employee and family)
• retirement benefits, including 401(k)
• paid holidays
• vacation
• compassionate and sick days