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

Role Summary

We are seeking a Manager in Life Sciences Commercial AI & Data Analytics to lead client engagements that use pharmaceutical commercial, real-world, and digital data to shape strategy and execution.

The role combines deep life sciences domain expertise with analytics leadership, client advisory, and practical knowledge of AI and modern data platforms. The Manager will frame complex business questions, design fit-for-purpose analytics and data solutions, guide multidisciplinary teams, and translate evidence into decisions across brand strategy, omnichannel engagement, customer analytics, launch, field effectiveness, and patient analytics.

The ideal candidate will be a credible commercial analytics advisor who can connect pharmaceutical market dynamics with data, technology, and delivery realities — ensuring that solutions are analytically sound, scalable, compliant, and useful to business stakeholders.

Key Responsibilities

Lead Commercial Analytics Strategy and Delivery

Lead analytics engagements addressing market opportunity, patient journeys, segmentation and targeting, omnichannel performance, launch readiness, field effectiveness, forecasting, and brand performance.
Frame ambiguous client challenges into clear hypotheses, analytical workplans, success measures, and decision points.
Guide the selection and interpretation of pharmaceutical commercial and real-world data, ensuring that populations, cohorts, business rules, metrics, and limitations are appropriate to the business question.
Own delivery quality, timelines, risks, and executive-ready outputs across multiple workstreams.

Shape AI and Advanced Analytics Solutions

Identify high-value applications of machine learning, generative AI, and advanced analytics across commercial functions, and distinguish viable opportunities from technology-led experimentation.
Direct the design and validation of solutions such as segmentation, propensity, next-best-action, forecasting, anomaly detection, NLP, and AI-assisted insight generation.
Ensure responsible AI practices, including appropriate data use, transparency, human oversight, performance monitoring, documentation, and compliance with client and regulatory expectations.
Explain model assumptions, limitations, and business trade-offs to senior stakeholders in accessible language.

Provide Data and Solution Architecture Direction

Guide teams in designing scalable analytical datasets, reusable data models, and robust ETL/ELT pipelines across claims, EHR/EMR, laboratory, SP/HUB, CRM, sales, access, and digital sources.
Set expectations for data quality, lineage, metadata, reproducibility, security, and documentation, and oversee resolution of complex data issues.
Partner with data engineers, architects, data scientists, and visualization specialists to align solution design with analytical needs and enterprise technology standards.
Promote reusable assets, modular code, automation, and cloud-based delivery approaches that improve quality and speed across engagements.

Advise Clients and Translate Evidence into Action

Act as a trusted advisor to commercial, marketing, sales, market access, analytics, and technology stakeholders.
Synthesize analytical findings into clear strategic implications, recommendations, and implementation priorities.
Lead workshops and senior stakeholder discussions, challenge assumptions constructively, and build alignment around decisions.
Ensure recommendations reflect pharmaceutical market dynamics, treatment pathways, customer needs, regulatory constraints, and operational feasibility.

Lead Teams and Build the Practice

Lead, coach, and review multidisciplinary teams, creating clarity on roles, standards, timelines, and expected outcomes.
Develop team capability across life sciences domain knowledge, analytics methods, AI, data engineering, quality assurance, and business storytelling.
Contribute to proposals, solution design, thought leadership, reusable accelerators, and the development of EY offerings.
Support account growth by identifying adjacent client needs and articulating differentiated, value-led solutions.

Experience

Required Skills & Experience

7–12 years of experience in life sciences commercial analytics, healthcare analytics, analytics consulting, data science, or a related field, including significant responsibility for client and team leadership.
Deep 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.
Strong understanding of the US pharmaceutical commercial model and familiarity with global markets, including commercial functions, patient and HCP journeys, therapeutic areas, launch dynamics, and regulatory and privacy considerations.
Proven leadership across multiple commercial use cases such as patient analytics, segmentation, targeting, omnichannel measurement, marketing mix, field effectiveness, forecasting, launch analytics, or market assessment.
Experience shaping and overseeing analytics solutions using SQL, Python/R, BI tools, and modern cloud data platforms; sufficient technical depth to review solution design and challenge delivery teams.
Experience directing data integration and engineering work, including analytical data models, ETL/ELT pipelines, data-quality controls, lineage, and reusable delivery assets.
Experience designing or governing machine-learning or generative-AI solutions, including model validation, adoption, monitoring, and responsible AI considerations.
Demonstrated experience managing senior client relationships, multidisciplinary teams, project economics, delivery risks, and competing priorities.

Domain And Consulting Skills

Deep pharmaceutical commercial and healthcare domain expertise, with credibility in senior business discussions.
Strategic, hypothesis-driven problem solving and the ability to structure complex, ambiguous client challenges.
Ability to connect commercial strategy, analytical methods, AI opportunities, data architecture, and implementation realities.
Strong executive communication, facilitation, negotiation, and storytelling skills.
High standards for analytical rigor, data quality, documentation, and delivery governance.
Inclusive people leadership, coaching, and performance-management capability across diverse and distributed teams.
Commercial acumen and the ability to identify client value, shape proposals, and expand relationships.

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.

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.

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

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