Principal Data Scientist

Description

The company runs an omnichannel engagement analytics program that uses data and analytics to improve how channel mix, content, field rep call planning and orchestration work together. The program sits within the APEX Enterprise Advanced Analytics and Innovation team.

This is the senior technical and scientific lead for the program's AI/ML and statistical work. You will set the multi-year data science direction for personalized commercial engagement and be responsible for the method choices and scientific quality behind it.

You report to the Associate Director, Data Science. You will advise commercial and analytics leaders on which problems to take on, argue for how AI delivers measurable business value, and work with product owners to turn that direction into solutions that scale.

The role calls for hands-on depth in applied machine learning, generative AI, causal inference and experimentation, plus the consulting skill to get a complex group of stakeholders behind one answer.

Responsibilities

• Own the multi-year data science vision and technical roadmap for omnichannel engagement analytics, anticipating where the business and AI research are heading.
• Find, size and rank the places where AI can create measurable commercial impact, build the business case, and help senior leaders decide where to invest.
• Build prototypes with AI-assisted development and agentic tools to test hypotheses and show value fast. Build LLM-based systems using advanced RAG and context engineering, backed by rigorous evaluation so that omnichannel recommendations are reliable at scale.
• Design predictive, causal, next-best-action, recommendation and sequential decision models that guide customer engagement and resource allocation, using complex data from multiple sources.
• Set the standard for measuring effectiveness, incrementality and business impact with experimental and quasi-experimental methods, so every AI investment is judged rigorously.
• Work with product owners to define the problem itself: agree on business outcomes, scope and success metrics, then turn them into scalable technical solutions.
• Coordinate across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab and external vendors. Turn requests into well-defined problems and settle competing priorities.
• Explain complex methods and findings as clear recommendations and stories for executives and non-technical audiences.
• Work with BTS, Digital Lab, engineering and platform teams to deploy, monitor and manage the full lifecycle of AI/ML solutions.
• Set community-wide practices for model development, code quality, reproducibility, peer review and responsible AI.
• Stay current on machine learning, generative AI and causal inference research. Bring new ideas to the team, push analytical debate, and represent the company's views inside and outside the organization.
• No formal direct reports. You will mentor and guide data scientists across the wider community and lead technical workstreams with external analytics vendors and partners, including checking deliverable quality and methods.

Requirements

• Bachelor's degree in statistics, mathematics, computer science, engineering or another quantitative field. A master's or PhD in a quantitative field is strongly preferred.
• 8+ years in data science, machine learning or applied science, or 6+ years with a PhD. Production models with a proven business impact.
• A record of setting technical direction for a portfolio of AI/ML solutions and shaping decisions made by senior business leaders.
• Experience building personalization, recommendation, decision optimization or marketing science solutions in any industry.
• Deep hands-on skill in causal inference and experimentation, including A/B tests and quasi-experimental methods.
• Hands-on use of generative AI and AI-assisted development tools, such as LLM APIs, AI coding assistants and agent frameworks, to prototype and deliver solutions. Be ready to walk through concrete examples in interviews.
• Expert in Python and SQL, with experience in deep learning frameworks such as PyTorch or TensorFlow and in distributed data processing.
• Experience putting AI/ML solutions into production in the cloud, including deployment, monitoring and lifecycle management.
• Experience leading work across complex, cross-functional stakeholder groups and presenting to executive audiences.
• Preferred: commercial analytics experience in pharmaceutical, biotech, healthcare or life sciences, including familiarity with IQVIA, Symphony Health, APLD or similar Rx, claims and engagement data.
• Preferred: omnichannel analytics experience, such as journey analysis, touchpoint measurement, closed-loop measurement or next-best-action for HCP or patient engagement.
• Preferred: advanced ML and optimization methods such as reinforcement learning, multi-armed bandits, transformers and other sequential or recommendation approaches.
• Preferred: experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines.
• Preferred: cloud ML platforms and MLOps tools such as Azure ML, Databricks and MLflow.
• Preferred: external visibility through conference talks, publications, patents, open-source work or recognized industry thought leadership.
• Preferred: experience in agile product development environments.

Conditions

Applies only where pay disclosure law requires it. The posted base pay range is the company's good-faith estimate for this grade at posting time. Actual pay depends on factors including location and may fall above or below the range, and the range may change.

The role is eligible for long-term incentive programs. Bonuses, incentives, benefits and other pay are discretionary and can change under applicable law until they are paid.

US and Puerto Rico only. The company is an equal opportunity employer.

Benefits

• Paid time off (vacation, holidays and sick leave), medical, dental and vision insurance, and a 401(k) for eligible employees.
• Eligible for long-term incentive programs.