The Head of Data Science & AI is a senior leadership position responsible for vision, strategy, and delivery of the company's data science and artificial intelligence initiatives. This role drives the development of scalable, actionable analytics that empower pharma and biotech customers to extract value from omics data through a cloud-based platform.

Key Responsibilities

Define and lead the long-term data science and AI strategy for the omics cloud platform, aligning with company vision and customer needs in the pharma and biotech sectors.
Build and scale a high-performing team of data scientists and AI/ML engineers, fostering a culture of innovation, scientific rigor, and collaborative problem-solving.
Drive the design, development, and deployment of advanced analytics, machine learning models, and AI-driven tools that enhance the accessibility and actionability of omics data for end users.
Oversee the architecture and maintenance of large-scale bioinformatics pipelines, ensuring robust, scalable, and secure handling of genomics/multiomics data in a cloud environment.
Collaborate cross-functionally with product management, engineering, sales, and customer teams to shape product direction and deliver customer-centric solutions.
Lead scientific and technical partnerships with industry, academia, and technology vendors to extend the platform’s capabilities and foster thought leadership in applied omics data science.
Ensure compliance with healthcare and data privacy regulations as applied to cloud-based omics workflows.
Mentor and develop emerging leaders within the data science organization, promoting professional growth and knowledge sharing throughout the team.
Represent the company as a scientific and technical leader in external forums, publishing, presenting, and engaging with the wider omics, AI, and pharma/biotech ecosystems.

Candidate Profile

PhD or equivalent experience in Bioinformatics, Computational Biology, Computer Science, Data Science, or a related field.
Demonstrated success in leading data science and AI teams in a cloud-first, SaaS, or multiomics research environment.
Deep expertise in machine learning, statistical modeling, and applied bioinformatics with real-world deployment on cloud platforms (AWS, GCP, Azure).
Familiarity with the regulatory and practical requirements of working with healthcare and omics data in the pharma/biotech context.
Proven ability to translate complex scientific and analytical ideas into actionable business and product outcomes for diverse stakeholders.
Excellent communication, leadership, and mentoring skills.
Track record of industry thought leadership, publication, or public speaking in the omics data science/AI space.

Hartmann Young

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