Remote Senior Knowledge Data Engineer | WFH

Position Title: Senior Data Knowledge Engineer - Remote | WFH

Job Overview

We are seeking a motivated and skilled Senior Data Knowledge Engineer with a passion for utilizing data to foster innovation in drug discovery. As an esteemed international data science service company, we specialize in exceptional data curation, governance, bioinformatics analysis, and more, serving a diverse clientele including pharmaceuticals, biotech, foundations, government, and healthcare.

Company Culture And Values

Our organization is dedicated to cultivating a dynamic and fast-paced work environment where employees are encouraged to excel both professionally and personally. We believe our team members are our most valuable assets, and we provide ample opportunities for continuous learning and career advancement.

Key Responsibilities

• Design and develop scalable data pipelines for the implementation of knowledge graph embeddings (KGE) in drug discovery contexts.
• Conduct thorough evaluations of KGE models to assess their efficacy in biomedical applications and enhance predictive performance.
• Engage in experimentation to explore how various training methodologies and settings impact model performance.
• Employ advanced techniques for hyperparameter optimization to enhance model accuracy and adaptability.
• Collaborate with interdisciplinary teams to ensure KGEs address real-world drug discovery challenges and comply with standards for equitable evaluation and reproducibility.
• Prepare and present findings and recommendations to refine KGE model assessment practices, contributing to the broader field of biomedical AI.
  
  

Required Skills

• Master's or Ph.D. in Data Science, Bioinformatics, Computer Science, or a closely related field.
• Demonstrated experience in developing and managing data pipelines and handling large datasets.
• Proficiency in Python programming, particularly with PyTorch and libraries such as PyG and PyKEEN.
• Practical knowledge of knowledge graphs, machine learning methodologies, and graph embedding models, with an emphasis on real-world applications.
• Familiarity with biomedical knowledge graph platforms, including Disqover, PrimeKG, Hetionet, or BioKG.
• Experience in fine-tuning parameters and optimizing models, especially utilizing Bayesian optimization methods.
• Strong analytical capabilities, with a talent for communicating complex concepts to both technical and non-technical audiences.
  
  

Qualifications

• Proven experience working with biomedical datasets or within the drug discovery sector is advantageous.
• Understanding of computational biology and systems pharmacology concepts is preferred.
• Familiarity with evaluation metrics and best practices to ensure model reproducibility in scientific research.
  
  

Career Growth Opportunities

We are committed to nurturing your professional development through various learning initiatives and career advancement pathways, enabling you to make a meaningful impact in the biomedical research and drug discovery landscape.

Networking And Professional Opportunities

Join our team and gain access to an expansive professional network where collaboration and skill development are fostered, enhancing your career trajectory in this vital field.

Compensation And Benefits

We offer a competitive salary alongside a comprehensive benefits package that promotes a culture of growth and collaboration. Join us in making a significant impact within the realm of biomedical research and drug discovery!

Employment Type: Full-Time