python developer in life sciences

EPAM delivers enterprise software products, open source solutions, and accelerators. Its Life Sciences and Healthcare projects focus on bioinformatics, data-driven solutions, computational biology, genomics, AI-enhanced drug discovery, and biomedical data platforms for pharmaceutical, biotech, and healthcare companies.

• Design, architect, and develop cloud-native, AI-driven Life Sciences solutions using Python;
• Build, optimize, and maintain data processing pipelines for large-scale biological and biomedical datasets, including genomics, transcriptomics, proteomics, and clinical data;
• Support the integration and application of Generative AI solutions, including LLMs and RAG, in bioinformatics and drug discovery workflows;
• Utilize computational and statistical techniques for high-throughput biological data, including sequence-based and omics data;
• Collaborate with bioinformaticians, computational biologists, data scientists, and domain experts to implement technical solutions based on scientific requirements;
• Facilitate technical improvements, review code, and ensure high-quality documentation and maintainability;
• Enhance AI components within client solutions and EPAM in-house platforms while following development best practices;
• Address challenges related to data scale, security, and performance in computational life sciences applications;
• Stay current with emerging trends in Life Sciences, AI, and cloud technologies and drive innovation within projects and teams.

• 3+ Years of experience in Python software engineering and practical exposure to Life Sciences, Healthcare, Bioinformatics, Computational Biology, or related domains;
• Proficiency in Python and modern web/API frameworks, including Django, Flask, or FastAPI;
• Experience with scientific and analytical Python libraries, including NumPy, Pandas, SciPy, and scikit-learn;
• Experience handling biological, biomedical, or clinical data, including NGS, transcriptomics, proteomics, multi-omics, or genomic data formats such as FASTQ, BAM, and VCF;
• Familiarity with integrating AI/ML models into production systems in data-intensive or regulated contexts;
• Strong understanding of software design principles, data structures, and algorithms;
• Hands-on experience with AWS, Azure, or GCP;
• Strong analytical and problem-solving skills, with the ability to contribute to technical discussions and solution design;
• Excellent communication skills and experience working in cross-functional, international teams;
• Fluency in English at a minimum B2 level, both written and spoken;
• Nice to have: A relevant M.Sc. or Ph.D. in Bioinformatics, Computational Biology, or a related quantitative field.

• No conditions specified