Risk Consulting - Regulatory Compliance - Life Sciences - Manager

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Our clients operate in a world where achieving high performance is just as important as the patients they serve. EY's Life Sciences team advises clients in the Life Sciences sector on strategic decisions to address risks affecting organizational performance and patient safety.

The Opportunity

The Life Sciences Risk Consulting Services team supports organizations operating in highly regulated environments where validated systems, reliable data, and regulatory compliance are critical to business performance and patient safety. In this role, you will lead client engagements and workstreams focused on the compliant development, implementation, and lifecycle management of artificial intelligence and machine learning solutions used in GxP-regulated processes and systems.

You will help clients establish and operationalize risk-based validation and assurance strategies for AI/ML solutions that may affect patient safety, product quality, data integrity, or regulatory decisions. This includes leading efforts to define intended use and assurance requirements, evaluate data and model performance, test AI-enabled workflows, establish lifecycle controls, and determine appropriate assurance as models, data, infrastructure, and business processes change.

The role involves leading multidisciplinary teams and working directly with client Quality, Regulatory, IT, Data Science, Engineering, Security, Privacy, and business stakeholders to integrate AI/ML validation and assurance into development, implementation, deployment, monitoring, and change-management practices. You will advise clients across manufacturing, laboratory, clinical, pharmacovigilance, quality, and regulatory operations while supporting audit and inspection readiness.

Your key responsibilities

Your time will be spent leading client engagement teams and workstreams delivering AI/ML validation and assurance projects in the life sciences domain. You will oversee assessments of GxP applicability, system criticality, and risk for AI/ML use cases, considering potential impacts on patient safety, product quality, data integrity, and regulated decisions. You will guide clients in defining intended use and context of use, regulated decisions supported by the solution, required human oversight, foreseeable failure modes, limitations, and prohibited uses.

You will define validation and assurance strategies and oversee the development, execution, and quality review of associated deliverables, including validation plans, requirements, risk assessments, requirements traceability matrices, test protocols, test evidence, deviations, and validation summary reports. You will guide teams in establishing scientifically and risk-appropriate acceptance criteria for data quality and model performance, including accuracy, sensitivity, specificity, precision, recall, F1 score, calibration, error rates, and other measures appropriate to the specific use case.

You will oversee assessments of data provenance, representativeness, completeness, labeling quality, lineage, transformation logic, training and test-data segregation, leakage risk, and compliance with data-integrity expectations. You will lead the design and review of functional, integration, regression, negative, boundary, security-role, audit-trail, data-reconciliation, and user-acceptance testing strategies for AI-enabled systems and workflows.

You will guide teams in challenging model reliability through reproducibility, robustness, bias, subgroup-performance, explainability, stress, and edge-case testing, ensuring identified limitations and residual risks are appropriately documented, communicated, and addressed. You will advise clients on production-monitoring strategies for model performance, data and concept drift, anomalous outputs, override patterns, human review, complaints, incidents, and other signals that may trigger investigation or revalidation.

You will establish appropriate governance and change-assessment approaches for model updates, retraining, prompt changes, knowledge-base changes, infrastructure changes, and vendor releases. You will oversee supplier assessments for externally developed models, cloud platforms, generative AI services, and software components, evaluate evidence gaps, and advise clients on proportionate compensating controls.

For generative AI and large language model use cases, you will lead assurance approaches addressing prompt and configuration controls, grounding and retrieval quality, output variability, inaccurate or unsupported outputs, sensitive-data handling, guardrails, and human verification. You will advise clients on deviations, investigations, corrective and preventive actions, periodic reviews, inspection readiness, and responses to Quality or regulatory observations involving AI-enabled systems.

You will be responsible for day-to-day engagement and workstream management, quality of deliverables, coordination of team activities, management of engagement risks and dependencies, and clear communication of findings and recommendations to client stakeholders. You will coach and develop junior professionals, provide technical review and direction, contribute to client relationships, and support the development of AI/ML validation and assurance capabilities within the Life Sciences practice.

Skills and attributes for success

• Deep grounding in GxP computerized-system validation, computerized software assurance, software development lifecycle controls, and Agile delivery models
• Strong understanding of machine learning development and evaluation, including data preparation, feature engineering, training, validation, testing, performance measures, and model limitations
• Demonstrated ability to evaluate AI/ML solutions for reliability, robustness, explainability, bias, data or concept drift, and appropriate human oversight
• Strong understanding of data provenance, lineage, quality, integrity, privacy, security, and fitness for intended use
• Ability to critically evaluate validation strategies, requirements, risk assessments, traceability, test design, technical evidence, deviations, and validation conclusions
• Ability to analyze complex data and test results and appropriately challenge technical evidence produced using Python, SQL, R, or comparable technologies
• Ability to translate evolving regulatory, Quality, and technical expectations into pragmatic and scalable validation and assurance approaches
• Strong engagement management and team leadership capabilities, including prioritizing work, directing multidisciplinary teams, managing risks and dependencies, and maintaining quality across concurrent activities
• Strong written, verbal, and executive-level communication skills, including the ability to clearly explain technical findings, model risk, and recommendations to Quality, business, technology, and regulatory stakeholders
• Ability to develop junior professionals and foster an innovative, inclusive, and team-oriented work environment

To qualify for the role you must have:

• A bachelor's degree in data science, computer science, engineering, statistics, life sciences, pharmacy, or a related discipline
• At least six years of relevant professional experience in computerized-system validation, quality assurance, software testing, data science, machine learning, technology risk, or a related field
• Meaningful experience leading projects or workstreams in a regulated life sciences environment, including GxP business processes, computerized systems, validation, risk management, or compliance programs
• Demonstrated experience developing and applying risk-based validation or computerized software assurance approaches and reviewing validation and testing documentation for quality and regulatory adequacy
• Practical knowledge of AI/ML development, testing, performance evaluation, lifecycle controls, and associated model risks
• Experience using analytical tools such as Python, SQL, R, or comparable technologies, or providing critical review and oversight of technical analyses generated using these tools
• Ability and willingness to work in a team-led and leader-enabled hybrid model, with the expectation that individuals in external, client-serving roles work together in person approximately 40% to 60% travel over the course of an engagement, project, or year.

Ideally, you'll also have:

• A master's degree in data science, computer science, engineering, statistics, life sciences, pharmacy, or a related discipline
• Experience applying GAMP 5, FDA Computer Software Assurance principles, 21 CFR Part 11, EU Annex 11, data-integrity principles, and quality risk management under ICH Q9 and ICH Q10
• Experience with validated platforms or processes such as manufacturing execution systems, laboratory information management systems, quality management systems, clinical systems, pharmacovigilance systems, regulatory content platforms, enterprise resource planning systems, Veeva Vault applications, or validation lifecycle management systems
• Familiarity with MLOps or LLMOps, model registries, version control, automated testing, cloud AI services, and controlled deployment pipelines
• Experience with AI/ML applications such as automated visual inspection, predictive maintenance, process monitoring, quality-event analytics, clinical or safety analytics, document intelligence, or generative AI assistants
• Experience managing multidisciplinary teams or client workstreams involving Quality, business, data science, engineering, and technology stakeholders
• Experience supporting health-authority inspections, internal audits, supplier audits, or remediation programs involving computerized systems, AI-enabled solutions, or data integrity

What we look for

We are interested in leaders who combine strong professional judgment, technical credibility, and disciplined engagement delivery with a commitment to quality and patient safety. Successful candidates can navigate ambiguity, challenge technical evidence constructively, identify material risks, and help clients reach well-supported decisions when technology and regulatory expectations continue to evolve.

We look for individuals who take accountability for team and client outcomes, develop others, build trusted relationships across Quality and technical organizations, and translate complex issues into clear recommendations and actions. You should be intellectually curious, comfortable operating across disciplines, and motivated to help life sciences organizations adopt innovative technologies responsibly while delivering measurable value and protecting patients.

What we offer you

At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers.

• The salary range for this job is:

• New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices - $137,900 to $229,700

• Bay Area California offices - $143,600 to $239,300

• All other offices locations in the US, including Sacramento - $114,800 to $210,600

• Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

Are you ready to shape your future with confidence? Apply today.

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• EY accepts applications for this position on an on-going basis.
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