About The Position

The Principal, AI and Automation Strategy Lead will work with statistical programmers to understand data requirements and deliver state-of-the-art solutions leveraging machine learning models and artificial intelligence. The position is responsible for identifying opportunities within statistical programming workflows to enhance operational efficiency and partnering with leadership to prioritize them. Then they will gather requirements, and either build agents using enterprise low/no code solutions or partnering with Data, Technology, and Engineering (DTE) to develop and deploy more advanced AI solutions.

Requirements

  • Understanding of statistical programming workflows and processes: should possess knowledge of the daily responsibilities and tasks of statistical programmers, including data preparation, analysis, and reporting. Familiarity with industry standards (e.g., CDISC, SDTM, ADaM) and regulatory requirements to identify opportunities for process optimization and the effective integration of AI tools to enhance efficiency and productivity.
  • Strong knowledge of data engineering, AI/ML frameworks (e.g., PyTorch, TensorFlow, etc.) and proficient in programming languages such as Python, R, SAS, and SQL for data processing.
  • Proficient in product and tool development with a strong grasp of UI/UX design principles to create intuitive and user-centric applications.
  • Understanding of Machine learning Models, Neural networks, NLP (Natural Language Processing), and NLG (Natural Language Generation).
  • Possesses expert knowledge of Small Language Models (SLMs), Large Language Models (LLMs), and LLM agents to enable intelligent automation and optimize statistical programming workflows.
  • Experienced in working with FAISS and other vector databases, including tokenization strategies, and Retrieval-Augmented Generation (RAG) frameworks for efficient semantic search and contextualized AI responses.
  • Knowledgeable about creation of no-code/low-code AI agents that automate tasks within statistical programming workflows, driving technological advancement, and enhancing departmental productivity.
  • Understanding of LLMOps and MLOps to operationalize AI and machine learning models, ensuring scalability, reliability, and seamless integration into statistical programming workflows.
  • Understanding of working in AWS cloud environment, including services such as SageMaker, EC2, and S3 for scalable machine learning workflows.
  • Strong problem-solving and analytical abilities.
  • Excellent communication skills for collaborating with stakeholders and bridging technical and domain teams.
  • Experience working in fast-paced environment.
  • Strong understanding of Generative AI ethics and governance frameworks: The candidate should demonstrate knowledge of ethical considerations, responsible AI practices, and governance frameworks related to the development, deployment, and use of Generative AI tools. This includes awareness of potential biases, data privacy concerns, transparency, accountability, and compliance with relevant regulatory and industry standards.
  • Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Life Sciences, or a relevant scientific field.
  • 5+ years of relevant experience with at least 3 years of experience in data engineering, data architecture, automation, and artificial intelligence (AI).

Nice To Haves

  • Familiarity with clinical or healthcare data is preferred.

Responsibilities

  • Collaborate with statistical programming leadership and Data, Technology, and Engineering (DTE) teams to continuously identify areas for improvement in statistical programming, capture requirements, propose technically sound solutions to enhance efficiency and innovation, and implement, prioritize and confirm ongoing enhancements.
  • Leverage a strong background in process excellence to identify inefficiencies, redesign workflows, and implement AI-driven solutions to optimize statistical programming processes.
  • Work with DTE to design and execute comprehensive AI/ML model validation strategies, including data splitting, metric selection, cross-validation, robustness testing, fairness audits, and post-deployment monitoring.
  • Experienced in providing training and technical support to end users for effective adoption and utilization of AI and automation solutions.
  • Drives innovation within Statistical Programming by identifying and implementing new tools, technologies, and methodologies to enhance efficiency and effectiveness, while fostering collaboration with peers across relevant functional areas.
  • Shapes the technical strategy of the Statistical Programming group by providing thought leadership, guiding the adoption of cutting-edge technologies, and encouraging a culture of creativity and continuous improvement within the team.

Benefits

  • The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards.
  • Some roles may also be eligible for overtime pay, in accordance with federal and state requirements.
  • At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations.
  • From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.

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What This Job Offers

Job Type

Full-time

Career Level

Principal

Number of Employees

5,001-10,000 employees

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