Overview
Job Description Orion Pharma is seeking an inspiring and visionary leader to serve as Head of Artificial Intelligence and Research Data Services, guiding our global team through a pivotal phase of digital transformation.
The Head of AI and Research Data Services in R&D will define and deliver the AI strategy across Oncology and Pain portfolios, accelerating discovery, translational medicine, and clinical development through high-impact, fit-for-purpose AI/ML solutions. This is a visionary, and proven leadership role: you will set direction, build and mentor a high-performing team, and personally drive the most critical technical and executional workstreams—turning data into decisions and decisions into measurable portfolio outcomes.
You will partner deeply with Oncology and Pain R&D leaders, Biometrics/Stats, Clinical Operations, Pharmacovigilance/Safety, Regulatory, Medical Affairs, and IT to deploy robust AI products and platforms that improve target and biomarker discovery, patient stratification, trial design and execution, endpoint measurement, and evidence generation. You will establish modern AI governance and Responsible AI practices aligned with regulated R&D environments and ensure scalable adoption across the organization.
Responsibilities
- Strategy & Portfolio Impact: Define an AI roadmap for R&D aligned to Oncology and Pain portfolio priorities (e.g., precision oncology, novel modalities, pain mechanisms, endpoints, patient subtypes).
- Identify, prioritize, and deliver AI initiatives with clear value cases (time-to-decision, probability of technical success, cycle-time reduction, cost efficiency, trial success metrics).
- Establish a use-case portfolio spanning discovery → clinical → real-world evidence, ensuring a balanced mix of quick wins and strategic platforms.
- Delivery of High-Value AI Use Cases: Lead (and when needed, personally architect) AI/ML solutions such as oncology biomarkers discovery, pain phenotyping, endpoint optimization, NLP for literature/notes, knowledge graphs for hypothesis generation, and governance in a regulated environment.
AI Platform, Data & MLOps
- Partner with Data Engineering/IT to build and evolve the R&D AI stack: data products, feature stores, model registries, reproducibility, and scalable compute.
- Establish MLOps/LLMOps practices (model versioning, monitoring, drift detection, validation, auditability).
- Ensure compliance with relevant regulations and quality expectations (e.g., GxP considerations where applicable, privacy, security, data integrity).
Governance, risk & culture
- Create and chair an AI governance framework: model risk classification, validation standards, documentation, bias testing, and human-in-the-loop controls.
- Define policies for vendor tools, generative AI usage, data access, IP protection, and secure development.
- Drive adoption with guardrails—enabling speed while protecting patients, science integrity, and reputation.
- Leadership, Team Building & Culture: Build and lead a cross-functional team of AI scientists, ML engineers, data scientists, product leads, and scientific translators; establish a culture of scientific rigor, rapid iteration, accountability, and collaboration.
- Coach stakeholders and elevate AI literacy across R&D; create “AI champions” embedded in Oncology and Pain functions.
Stakeholder & External Partnerships
- Serve as a trusted partner to therapeutic area heads, Translational Medicine, Clinical Development, Biometrics, and Regulatory.
- Translate R&D needs into technical solutions and ensure adoption through clear workflows and training.
- Communicate results effectively to executives and governance bodies; make complex topics accessible and decision-relevant.
- Build strategic collaborations with academia, AI vendors, consortia, and CRO/CDMO partners.
- Evaluate and integrate external datasets (RWD, imaging, genomics) and technologies while ensuring quality, privacy, and contracts align with strategy.
- Represent the company externally (conferences, publications, partner discussions) as an AI leader in Oncology and Pain R&D.
Location
The role can be based in Cambridge, Massachusetts (USA); Cambridge (UK); or Espoo, Finland, within the Research & Development (R&D) organization, and reports directly to the Chief Medical Officer, Oncology Therapy Area.
What We Offer
- The opportunity to shape the future of pharmaceutical research in a global, agile, and entrepreneurial environment.
- Generous health, welfare, and development benefits.
- A leadership role with significant influence on Orion’s sustainability agenda, patient safety, and ethical standards.
Learn More About Orion Pharma’s Mission And Culture
Orion as an employer and / or Scientist relocation journey to Finland
Our expectations
- PhD, MD, or equivalent degree in Computer Science, Machine Learning, Statistics, Bioinformatics/Computational Biology, Biomedical Engineering, or a related field with exceptional, demonstrated industry impact and leadership.
- Preferred: formal training or substantial experience in clinical research, oncology biology, neuroscience/pain biology, or translational medicine.
Experience
- 10+ years relevant experience applying AI/ML in life sciences, healthcare, biotech/pharma R&D, or adjacent regulated domains; 5+ years leading teams and delivering products.
- Proven track record deploying AI systems beyond prototypes (productionization, adoption, measurable impact).
- Demonstrated experience with multimodal biomedical data (e.g., EHR/RWD, imaging, omics, wearable/digital data, assay data, clinical trial data).
- Strong background partnering with Clinical Development, Biometrics/Stats, Translational Medicine, and/or Discovery teams.
- Experience establishing MLOps practices and governance in environments requiring traceability and documentation.
- Exposure to oncology and/or pain programs (preclinical to clinical). Deep expertise in one with credible breadth across the other is acceptable.
- Experience with trial design optimization, adaptive designs, enrichment strategies, or biomarker-driven development.
- Familiarity with pathology/radiology ML, digital endpoints, or sensor-derived biomarkers.
- Publications, patents, or conference presence in applied AI for biomedicine.
- Experience with knowledge graphs, graph neural networks, or multimodal foundation models in life sciences.
- Prior experience leading through an AI transformation or scaling an AI CoE in R&D.
- Deep knowledge of modern ML (supervised/unsupervised, deep learning, NLP/LLMs, causal inference, time-to-event modeling, multimodal learning).
- Ability to review code/architecture, challenge assumptions, and drive practical engineering outcomes.
- Strong experimental design mindset; understands data leakage, bias, confounding, validation, and generalizability.
- Expertise in cloud-based data solutions, ETL pipeline development, and modern analytics tools (Azure, SAS, R, Python, SQL).
- Strong knowledge of global data standards and regulatory frameworks.
- Hands-on experience with research-phase data tools and platforms, including: Electronic Lab Notebooks, Laboratory Information Management Systems, Bioinformatics workflows, Omics analysis platforms, High-performance computing (HPC) environments, Version-controlled research workflows (Git/GitHub/GitLab), Data visualization and exploration tools, Model-building and experimentation platforms, and Preclinical study data systems.
Visionary Leadership
A visionary, hands-on leader who defines a compelling AI strategy tightly linked to portfolio priorities and scientific hypotheses, designs scalable operating models (platform + products + embedded translators), and anticipates where AI can transform R&D decision-making beyond automation to insight. Prioritizes and turns ambiguity into clear roadmaps, milestones, and measurable outcomes—prototyping fast and industrializing deliberately—while delivering adoption-ready solutions through workflow integration, training, monitoring, and lifecycle management. Communicates complex AI topics effectively to scientific, clinical, and executive audiences, leads through influence in a matrix, resolves conflict, and aligns stakeholders with credibility across domain and technical teams. Sets high standards for reproducibility, documentation, privacy, security, and model risk, champions Responsible AI with patient-centered principles, builds and develops high-performing teams and culture, stays scientifically grounded to avoid “AI theater,” and measures success by better portfolio decisions and patients helped.
How To Apply
If this opportunity excites you, we encourage you to apply! Please submit your cover letter and CV by May 17th, 2026. We typically review applications during the application period and may start interviewing candidates before the deadline. Therefore, please send your application as soon as possible.
The expected salary range for this position depends on the country the role will be based. Final compensation will depend on skills, experience, and job-related qualifications.
Approved medical examination which also includes drug testing is required prior to the employment. We will also carry out a security clearance prior to the employment for the selected person.
Unit Description
Orion’s pharmaceutical innovations are created within its R&D organization. We employ around 400 professionals in drug discovery and development. We work globally: in Espoo and Turku in Finland, in Cambridge and Nottingham in England and in Cambridge, MA, USA. Orion R&D and the Innovative Medicines business division are dedicated to transforming to become a global player in the pain and oncology therapy areas.
About Us
Orion Pharma is a globally operating Nordic pharmaceutical company – a builder of well-being for over a hundred years. We’re home to more than 4,000 Orionees around the world and are known as a responsible employer. Our culture values every voice, encourages growth, and supports collaboration. Our core therapy areas in R&D are oncology and pain. We offer careers with a clear purpose: empowering people to live their lives to the fullest.
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