EY - GDS Consulting - AI And DATA -Life Sciences Commercial -Senior

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Job Description – Senior: Life Sciences Commercial AI & Data Analytics

Role Summary

We are seeking a Senior Consultant in Life Sciences Commercial AI & Data Analytics with strong pharmaceutical domain knowledge and hands-on experience using commercial and real-world data to support business decisions.

The role involves working with global EY teams and clients to solve commercial challenges across brand strategy, omnichannel engagement, customer analytics, launch, field effectiveness, and patient analytics. The successful candidate will combine an understanding of the US and global pharmaceutical landscape with practical analytics, AI, and data-engineering skills to create reliable datasets, models, dashboards, and actionable recommendations.

The ideal candidate will bring strong knowledge of pharmaceutical data sources and commercial processes, the ability to translate business questions into structured analyses, and sufficient engineering fluency to build reusable data pipelines and analytics products.

Key Responsibilities

• Deliver Commercial and Real-World Data Analytics
  • Analyze pharmaceutical commercial and real-world data to address questions related to market opportunity, customer segmentation, patient journeys, omnichannel performance, launch readiness, field effectiveness, and brand performance.
  • Assess data sources for fitness and feasibility; define populations, cohorts, business rules, metrics, and study-specific variables.
  • Build analytical datasets by integrating, transforming, cleaning, and validating claims, EHR/EMR, laboratory, specialty pharmacy/HUB, CRM, sales, and digital engagement data.
  • Develop analytical frameworks and hypotheses, perform exploratory and statistical analyses, and execute modelling using SQL and Python/R.
  • Apply rigorous quality checks and maintain traceable, reproducible analytical outputs.

• Apply AI and Advanced Analytics
  • Use machine learning and AI techniques, where appropriate, for segmentation, propensity, next-best-action, forecasting, anomaly detection, natural-language processing, and insight generation.
  • Support the responsible use of generative AI in commercial analytics, including prompt design, output validation, human review, documentation, and protection of sensitive information.
  • Evaluate model performance and business relevance, explain limitations, and avoid using advanced techniques where simpler approaches better answer the client question.

• Build Data Pipelines, Dashboards and Reusable Assets
  • Develop and maintain modular SQL/Python pipelines that convert raw source data into analysis-ready datasets and repeatable outputs.
  • Support ingestion, mapping, data-quality controls, metadata, documentation, and orchestration using cloud and ETL/ELT tools.
  • Build dashboards in Power BI or Tableau and automate recurring reporting workflows for commercial stakeholders.
  • Contribute reusable code, data models, accelerators, and technical documentation to team repositories.

• Translate Analytics into Business Recommendations
  • Convert analytical outputs into concise, commercially relevant insights and implications for marketing, sales, market access, launch, and strategy teams.
  • Create leadership-ready presentations, dashboards, and narratives that clearly distinguish evidence, assumptions, limitations, and recommendations.
  • Connect findings to pharmaceutical market dynamics, treatment pathways, customer behavior, channel strategy, and operational feasibility.

• Collaborate with Clients and Delivery Teams
  • Work with EY global teams and client stakeholders to clarify business questions, scope analyses, and align on timelines, risks, dependencies, and quality standards.
  • Present methods and insights clearly to technical and non-technical audiences across time zones.
  • Mentor junior analysts on domain context, analytics methods, coding practices, quality checks, and business storytelling.

Required Skills & Experience

Experience

• 3–7 years of experience in life sciences commercial analytics, healthcare analytics, analytics consulting, data science, or a related field.
• Hands-on experience with pharmaceutical datasets such as IQVIA, Komodo, Symphony, Optum, HealthVerity, TriNetX, EHR/EMR, claims, SP/HUB, laboratory, CRM, sales, market access, and digital engagement data.
• Understanding of the US pharmaceutical commercial model and familiarity with global markets, including key stakeholders, patient and HCP journeys, therapeutic areas, and regulatory and privacy considerations.
• Experience delivering one or more commercial use cases such as patient analytics, segmentation, targeting, omnichannel measurement, marketing mix, field effectiveness, forecasting, launch analytics, or market assessment.
• Hands-on SQL proficiency and working knowledge of Python or R; experience creating robust analytical datasets and reusable code.
• Experience with Power BI or Tableau and familiarity with cloud data platforms and ETL/ELT tools such as Azure Data Factory, AWS Glue, Databricks, Snowflake, Talend, or equivalent.
• Exposure to machine learning, generative AI, or advanced analytics in a business context, with an understanding of model validation and responsible AI practices.

Domain and Consulting Skills

• Strong pharmaceutical commercial and healthcare domain knowledge, with the ability to connect data patterns to real business context.
• Hypothesis-driven problem solving and the ability to independently structure ambiguous analytical questions.
• Ability to translate complex analyses into clear business narratives and practical recommendations.
• Strong attention to detail, data-quality mindset, and ability to manage multiple workstreams under tight deadlines.
• Clear written and verbal communication and effective collaboration with cross-functional and geographically distributed teams.
• Curiosity about emerging AI, data, and digital capabilities, balanced with sound judgment about their practical application.

Educational Qualifications

• Bachelor’s or Master’s degree in life sciences, engineering, data science, business, or a related discipline.
• An MBA or advanced degree in pharma, healthcare, analytics, or a related field is preferred but not mandatory.

Preferred (Good-to-Have)

• Experience supporting US or global pharmaceutical commercial teams.
• Experience in oncology or another complex specialty therapeutic area.
• Experience contributing to consulting proposals, reusable accelerators, or analytics products.

What we look for

We look for people who can develop and implement creative solutions to challenging problems and work well with teams to accomplish them. We value an entrepreneurial spirit: people who are innovative by nature and continually explore better approaches, products, services, and technologies.

Helping clients solve complex problems and implement practical solutions requires intellectual rigor, commercial judgment, curiosity, and a clear understanding of what works in real delivery environments. We seek people who lead themselves and others effectively, foster inclusive teamwork, and consistently deliver high-quality outcomes.

What working at EY offers

At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies, and the work we do with them is as varied as they are. You will work on inspiring and meaningful projects, supported by education, coaching, and practical experience that enables your continued development.

You will be part of an interdisciplinary environment that emphasizes high quality, knowledge exchange, and opportunities to build new skills and progress your career.

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