AI & Real World Analytics Senior Manager
Vertex Pharmaceuticals
August 09, 2026
Remote friendly (Boston, MA)
United States
IT
General Summary:
- Lead and advance the RWA team’s AI and automation capabilities by developing and optimizing real-world data analysis processes. Deep dive into Real-World Data (RWD) to generate data expertise, actionable insights, and optimal data-use strategies. Identify opportunities to enhance automation, standardization, and simplification; gather requirements and build agents via enterprise low/no-code solutions or partner with Data, Technology, and Engineering (DTE) to develop and deploy advanced AI solutions.
Key Duties and Responsibilities:
- Lead RWE analysis projects incorporating AI/ML.
- Optimize analytics project workflows and data source intake/hosting workflows with AI/ML solutions in partnership with DTE.
- Streamline project management (request handling, execution, delivery) to automate tracking, resourcing, and milestone communication.
- Enhance and standardize process documentation using AI/ML to identify analytic program gaps and recommend best practices.
- Identify automation opportunities (e.g., DAP validation, medical code list searching, programming plan/code generation, QC, result cross-checking). Manage/support internally developed AI solutions (access, runbooks, operational workflows).
- Apply advanced AI/ML to generate insights from RWD (benchmarks, representativeness, gaps/overlaps) and propose solutions to address data limitations.
- Partner with DTE on AI/ML environment; implement standards and observability with DTE AI Engineering/AI Operations.
- Design/execute AI/ML model validation (splitting, metrics, cross-validation, robustness, fairness audits, post-deployment monitoring).
- Provide training and technical support for adoption.
- Provide thought leadership to shape technical strategy and drive continuous improvement.
- Understand Generative AI ethics and governance (bias, privacy, transparency, accountability, compliance).
Knowledge and Skills:
- Hands-on AI/ML (supervised/unsupervised/reinforcement; neural networks, random forests).
- Experience deploying AI applications on AWS, GCP, Azure; expertise in Azure AI Foundry.
- Proficiency in Python, SQL, SAS, R; familiarity with AWS computational environments.
- Knowledge of healthcare claims and EHR; exposure to major U.S. RWD sources.
- Knowledge of statistical modeling and observational research.
- Problem-solving/analytical abilities; strong communication.
Education and Experience:
- Advanced degree in epidemiology, biostatistics, math, data science, or similar.
- 5+ years observational research in life sciences (or relevant academic/government/consulting); 3+ years AI/ML-related data engineering and automation.
Benefits:
- Annual bonus and annual equity awards.
- Medical, dental, vision; generous paid time off (incl. week-long company shutdown in Summer and Winter); educational assistance/student loan repayment; commuting subsidy; matching charitable donations; 401(k).
- Lead and advance the RWA team’s AI and automation capabilities by developing and optimizing real-world data analysis processes. Deep dive into Real-World Data (RWD) to generate data expertise, actionable insights, and optimal data-use strategies. Identify opportunities to enhance automation, standardization, and simplification; gather requirements and build agents via enterprise low/no-code solutions or partner with Data, Technology, and Engineering (DTE) to develop and deploy advanced AI solutions.
Key Duties and Responsibilities:
- Lead RWE analysis projects incorporating AI/ML.
- Optimize analytics project workflows and data source intake/hosting workflows with AI/ML solutions in partnership with DTE.
- Streamline project management (request handling, execution, delivery) to automate tracking, resourcing, and milestone communication.
- Enhance and standardize process documentation using AI/ML to identify analytic program gaps and recommend best practices.
- Identify automation opportunities (e.g., DAP validation, medical code list searching, programming plan/code generation, QC, result cross-checking). Manage/support internally developed AI solutions (access, runbooks, operational workflows).
- Apply advanced AI/ML to generate insights from RWD (benchmarks, representativeness, gaps/overlaps) and propose solutions to address data limitations.
- Partner with DTE on AI/ML environment; implement standards and observability with DTE AI Engineering/AI Operations.
- Design/execute AI/ML model validation (splitting, metrics, cross-validation, robustness, fairness audits, post-deployment monitoring).
- Provide training and technical support for adoption.
- Provide thought leadership to shape technical strategy and drive continuous improvement.
- Understand Generative AI ethics and governance (bias, privacy, transparency, accountability, compliance).
Knowledge and Skills:
- Hands-on AI/ML (supervised/unsupervised/reinforcement; neural networks, random forests).
- Experience deploying AI applications on AWS, GCP, Azure; expertise in Azure AI Foundry.
- Proficiency in Python, SQL, SAS, R; familiarity with AWS computational environments.
- Knowledge of healthcare claims and EHR; exposure to major U.S. RWD sources.
- Knowledge of statistical modeling and observational research.
- Problem-solving/analytical abilities; strong communication.
Education and Experience:
- Advanced degree in epidemiology, biostatistics, math, data science, or similar.
- 5+ years observational research in life sciences (or relevant academic/government/consulting); 3+ years AI/ML-related data engineering and automation.
Benefits:
- Annual bonus and annual equity awards.
- Medical, dental, vision; generous paid time off (incl. week-long company shutdown in Summer and Winter); educational assistance/student loan repayment; commuting subsidy; matching charitable donations; 401(k).