Chief Data Scientist – Artificial Intelligence in Biomedicine

1 day ago


Bengaluru, Karnataka, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Transforming Life Sciences with Machine Learning Expertise

">Job Overview:

This role offers an exciting opportunity to drive transformative insights from multi-omics and biomedical data.


The successful candidate will design, implement, and optimize machine learning algorithms for analyzing biological data, including genomics, transcriptomics, mass spec, and imaging datasets.


  • Develop approaches to integrate diverse data types (e.g., multi-omics, clinical, imaging) to derive meaningful biological insights.
  • Stay updated with state-of-the-art ML methods and their applications in life sciences to propose innovative solutions.
  • Work closely with bioinformaticians, data scientists, and domain experts to ensure seamless integration of ML models into workflows.
  • Optimize and deploy ML models on cloud platforms for scalable analysis.
  • Collaborate on preprocessing, feature engineering, and quality control of large, noisy biological datasets.

Qualifications:
  • Master's or Bachelor's degree in Machine Learning, Computer Science, Bioinformatics, Computational Biology, or a related field.
  • Solid understanding of machine learning algorithms (e.g., supervised, unsupervised, deep learning) and statistical methods.
  • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Strong problem-solving skills with an aptitude for interpreting complex biological data.
  • Excellent communication and interpersonal skills, with the ability to work effectively in a collaborative environment.
  • Experience working with cloud technologies and scalable computing platforms.

Benefits:
  • Contribute to groundbreaking research in GenAI in life sciences R&D across leading BioPharma companies.
  • Collaborate with experienced professionals in the field to develop innovative solutions.
  • Opportunities for professional growth and development in a dynamic industry.

Additional Requirements:
  • Experience with biological datasets (e.g., NGS, proteomics, or imaging) and applying ML to multi-omics data integration.
  • Familiarity with biomedical ontologies, pathway analysis, or systems biology approaches.
  • Strong publication record in ML or bioinformatics journals.

Elucidata is at the forefront of driving GenAI in life sciences R&D.



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