Vice President of Data Science and AI

Grayson Search Partners; Boston; On-site; GBP 90,000 - 130,000; Full time

Job summary

A leading market player in regulatory-grade data management seeks a Vice President of Data Science & AI. The successful candidate will spearhead the organization's AI strategy, driving product innovation and operational efficiency. You will collaborate with diverse teams, translating complex data into actionable insights and scalable solutions to enhance client engagement in the biopharmaceutical sector.

Qualifications

• Proven success in commercial AI/data science applications within the pharmaceutical or life sciences sectors.
• Experience in building and mentoring high-performing teams.
• Strong communication skills for engaging with executive stakeholders.

Responsibilities

• Lead AI strategy and data science initiatives driving innovation across platforms.
• Design and implement algorithms for large-scale structured/unstructured datasets.
• Build and mentor a high-performing data science and AI team.

Skills

Leadership

Communication

Strategic Execution

Cultural Agility

Domain Expertise

Tools

SQL

Python

Job description

Vice President, Data Science & AI

About Us:

Our client is a market leader in regulatory-grade data management software and services for the biopharmaceutical industry. Their flagship platform, ingests, processes, and analyzes clinical trial data to accelerate FDA submissions.

Position Summary:

As Vice President of Data Science & AI, you will lead our organization’s AI strategy and data science initiatives, driving innovation across our platform and services. This executive-level role will shape the vision, roadmap, and execution of AI-driven product development, customer intelligence, and operational efficiency—positioning our client at the forefront of data innovation in life sciences.

Key Responsibilities:

AI & Product Strategy

• Partner with Product, Business Development, and Strategic Partners to deeply understand client use cases and uncover opportunities for AI-driven solutions.
• Translate business challenges into scalable data models and algorithms across the full data science lifecycle—from data engineering to model deployment.
• Use customer data to derive behavioral insights and translate findings into product innovation and experience enhancement.
• Apply advanced statistical methods and machine learning techniques to build high-impact solutions that enhance both clinical and commercial outcomes.

Product Innovation & Development

• Lead the advancement of the platform using AI, data science, and advanced analytics.
• Design and implement algorithms using large-scale structured and unstructured data sets (e.g., clinical trial data, RWE, regulatory databases).
• Employ technologies such as SQL, Python, and related tools to develop scalable, production-ready solutions.
• Oversee a team of data scientists and technical experts to ensure project success and knowledge growth.

Customer & Market Impact

• Implement predictive models and AI capabilities that improve customer targeting, engagement, and satisfaction.
• Anticipate and proactively address client needs through tailored, data-informed solutions.

Operational Analytics & Insights

• Define, monitor, and report on key performance indicators (KPIs) to assess AI project impact.
• Quantify the return on investment (ROI) for major AI and data science initiatives to inform executive decisions.

Leadership & Team Building

• Build, lead, and mentor a high-performing data science and AI team with a focus on innovation, collaboration, and excellence.
• Cultivate a culture of continuous learning, experimentation, and cross-functional alignment.
• Collaborate with teams across the business to develop descriptive, prescriptive, and predictive analytics that solve complex problems.

Operational Excellence

• Ensure robust data governance, quality, and regulatory compliance across all initiatives.
• Foster an innovation-first mindset while installing scalable systems and processes to support growth and maturity.
• Drive organizational transformation by building team capabilities and improving employee engagement scores.

Required Experience & Competencies

• Domain Expertise: Proven success developing and deploying commercial AI/data science applications in the pharmaceutical, healthcare IT, or life sciences sector.
• Leadership: Experience building teams, mentoring talent, and introducing best practices in environments with low-to-mid process maturity.
• Strategic Execution: Strong ownership mindset, comfortable navigating ambiguity, making data-informed decisions, and executing quickly with limited structure.
• Communication: Clear, confident, and data-driven communicator with experience presenting to executive stakeholders, boards, and cross-functional teams.
• Entrepreneurial Drive: Thrives in fast-paced, PE-backed, growth environments. Demonstrates a bias for action and adaptability typical of early-stage or scaling ventures.
• Cultural Agility: Comfortable leading through organizational change and building capabilities amid shifting priorities.