Staff Data Scientist, Life Sciences AI (RWE & Meta-Analysis)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Scientist, Life Sciences AI (RWE & Meta-Analysis) in the United States.

We are seeking a highly skilled Staff Data Scientist to drive AI-powered innovation in the life sciences and healthcare domains. This role focuses on designing and developing scalable tools for meta-analysis, systematic reviews, and real-world evidence (RWE) generation. You will collaborate with cross-functional teams to translate complex statistical and clinical workflows into client-facing AI solutions. The ideal candidate combines deep scientific expertise, product-oriented thinking, and experience building cloud-based ML pipelines and MLOps practices. Your work will leverage LLMs, NLP, and information extraction to automate literature review, data curation, and evidence synthesis. This is a high-impact position where you will influence the development of AI-driven analytics platforms that support critical decision-making in healthcare and life sciences.

Accountabilities:

• Design and implement AI-driven software tools that enable meta-analysis, systematic reviews, and RWE generation.
• Translate complex statistical and meta-analytic workflows into scalable, automated product features.
• Collaborate with engineers, domain experts, and stakeholders to ensure scientific rigor, usability, and compliance.
• Build and maintain scalable AI and data pipelines, integrating structured, unstructured, and real-world datasets.
• Leverage LLMs, prompt engineering, and information extraction techniques to automate literature review and evidence synthesis.
• Implement modern MLOps practices, including CI/CD, testing, monitoring, and version control for reliable deployments.
• Evaluate emerging AI/ML technologies, drive proof-of-concept initiatives, and contribute to the technical roadmap.
• Mentor team members and promote a culture of scientific excellence, innovation, and continuous learning.

• PhD preferred (or Master’s with 8+ years of experience) in Biostatistics, Bioinformatics, Computer Science, Health Informatics, or related field.
• Expertise in statistical modeling, meta-analysis methodology, and evidence synthesis relevant to RWE.
• Strong background in NLP, LLMs, prompt engineering, and information extraction from scientific literature.
• Proficiency in Python and ML/NLP frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, and scikit-learn.
• Experience designing and deploying AI-driven analytical tools or platforms, including LLM-based workflows.
• Familiarity with vector databases, knowledge graphs, and semantic data modeling for biomedical information.
• Solid understanding of experimental design, statistical inference, and validation methods.
• Experience integrating biomedical or healthcare data sources (e.g., literature, EHR, claims, registries).
• Knowledge of data privacy, ethics, and regulatory standards in healthcare (e.g., HIPAA).
• Strong collaboration, communication, and mentoring skills; experience with scientific publications or presentations is a plus.
• Innovative, solution-oriented mindset with a passion for advancing evidence generation in life sciences.

• Competitive salary range: $170,000 – $250,000 per year.
• Health, dental, and vision insurance coverage.
• Retirement plan options with employer contributions.
• Paid time off and holidays to support work-life balance.
• Professional development opportunities and skill-building resources.
• Flexible, remote-friendly work environment.
• Opportunities to work on cutting-edge AI/ML tools in healthcare and life sciences.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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