Bioinformatics Data Scientist at Clear Point Consultants

About Us:

Our next-generation pharmaceutical client is at the forefront of innovative drug discovery, leveraging cutting-edge technologies to tackle the world’s most pressing health challenges. They are a multidisciplinary team of scientists, engineers, and bioinformaticians committed to developing transformative therapies. Join us in our mission to revolutionize healthcare through data-driven insights.

Job Overview:

We are seeking a highly motivated PhD-level Bioinformatics Data Scientist with expertise in Knowledge Graph Embedding (KGE) model development to support our drug discovery pipeline. The successful candidate will play a pivotal role in developing and implementing KGE models to identify novel therapeutic targets, drug-repurposing opportunities, and insights into biological pathways. You will work closely with cross-functional teams, including AI/ML experts, computational biologists, and drug discovery scientists, to accelerate the identification of new treatment possibilities.

Key Responsibilities:

• Design, develop, and optimize Knowledge Graph Embedding (KGE) models for analyzing biomedical and molecular data in the context of drug discovery.
• Integrate and analyze large-scale biological datasets (e.g., omics, chemical, and clinical data) within a knowledge graph framework.
• Collaborate with domain experts to generate hypotheses for drug repurposing and target discovery using KGE models.
• Develop novel algorithms and pipelines to assess the structure and function of biological networks related to disease mechanisms and drug efficacy.
• Perform validation and benchmarking of models using public and proprietary datasets.
• Stay up to date with advances in computational biology, KGE methodologies, and AI/ML applications in life sciences.
• Communicate findings and insights to stakeholders through presentations, reports, and scientific publications.

Required Qualifications:

• PhD in Bioinformatics, Computational Biology, Data Science, Machine Learning, or a related field.
• Strong expertise in Knowledge Graph Embedding (KGE) models and their applications in life sciences.
• Proficiency in programming languages such as Python, R, Java, or similar, with experience in libraries/frameworks for KGE (e.g., PyKEEN, DGL-KE).
• Deep understanding of biological data sources (e.g., genomics, proteomics, metabolomics) and their integration into knowledge graphs.
• Hands-on experience with drug discovery workflows, including target identification and drug repurposing.
• Strong statistical, machine learning, and deep learning skills, with an ability to interpret complex biological datasets.
• Experience working with high-performance computing environments and cloud-based data platforms (AWS, GCP, Azure, etc).
• Strong communication skills, with the ability to work collaboratively in an interdisciplinary environment.

Preferred Qualifications:

• Familiarity with graph databases (e.g., Neo4j, RDF stores) and semantic web technologies.
• Experience in drug discovery or pharmaceutical R&D environments.
• A strong publication record in bioinformatics, computational biology, or related fields.
• Experience with natural language processing (NLP) and text mining in biomedical literature is a plus.

Why Join Us?

• Opportunity to work on cutting-edge projects with the potential to significantly impact human health.
• Collaborative and innovative work environment with world-class scientists and technologists.
• Competitive salary and comprehensive benefits package.
• Opportunities for professional development, including attending conferences and publishing your work.

If you are passionate about using cutting-edge bioinformatics and data science techniques to make a difference in drug discovery, we encourage you to apply.

Please apply ASAP if you are interested!