Head of AI and Research Data Services, Oncology

Orion

Head of AI and Research Data Services at Orion Pharma, shaping AI strategy for Oncology and Pain research. Leading global team through digital transformation with a focus on impactful AI/ML solutions.

Posted 5/5/2026full-timeCambridge • Massachusetts • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AzureCloudETLPythonSQL

About the role

Key responsibilities & 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.
Lead (and when needed, personally architect) AI/ML solutions such as:
Oncology: multimodal biomarker discovery (omics + imaging + clinical), pathology/radiology ML, response prediction, resistance mechanisms, molecular stratification, site selection and enrollment optimization.
Pain: phenotyping and subtyping, digital biomarkers, endpoint optimization (PROs, wearable data), mechanistic modeling, responder prediction, trial enrichment strategies.
Cross-portfolio: NLP for literature/clinical notes, knowledge graphs for hypothesis generation, causal inference for RWE, safety signal augmentation, protocol optimization and feasibility.
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).
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.
Build and lead a cross-functional team of AI scientists, ML engineers, data scientists, product leads, and scientific translators.
Serve as a trusted partner to therapeutic area heads, Translational Medicine, Clinical Development, Biometrics, and Regulatory.
Build strategic collaborations with academia, AI vendors, consortia, and CRO/CDMO partners.
Represent the company externally (conferences, publications, partner discussions) as an AI leader in Oncology and Pain R&D.

Requirements

What you’ll need

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.
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 (Spotfire, LiveDesign, etc.)
Model‑building and experimentation platforms
Preclinical study data systems

Benefits

Comp & perks

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.

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AIMLmultimodal databiomedical dataMLOpsdeep learningNLPcausal inferenceexperimental designdata analysis

Soft Skills

leadershipcollaborationcommunicationstrategic thinkingproblem-solvingteam buildingproject managementcritical thinkingadaptabilitymentorship

Certifications

PhDMD