Python Developer

Role & responsibilities:

• Design, develop, and implement machine learning models and algorithms tailored to healthcare applications.
• Collaborate with healthcare professionals and data analysts to identify opportunities for machine learning solutions in patient diagnosis, treatment planning, and healthcare operations.
• Perform data preprocessing, feature engineering, and analysis of healthcare datasets, including electronic health records (EHR) and medical imaging data.
• Work closely with data engineers to ensure efficient data pipelines for model training and deployment.
• Conduct experiments, model training, and hyperparameter tuning to achieve optimal performance while adhering to regulatory compliance and privacy standards.
• Stay current with the latest advancements in machine learning, AI, and healthcare informatics.
• Proficient in developing Python-based AI modules for real-time data processing and decision-making.
• Designed and implemented RESTful APIs for seamless integration of AI models with enterprise applications, enhancing system interoperability.
• Built and fine-tuned Generative AI models, leveraging state-of-the-art architectures for natural language processing, data generation, and predictive analytics.
• Developed and trained CNN-based models for image classification, object detection, and medical imaging, delivering high accuracy and efficiency in healthcare AI solutions.
• Expertise in knowledge graph-based queries

Preferred candidate profile:

• Bachelor's or Master's degree in Computer Science or Data Science or Healthcare Informatics or a related field.
• A minimum of 4.5 years of experience as a python based machine learning developer.
• Proficiency in Python programming and experience with relevant libraries, including TensorFlow, PyTorch, scikit-learn, and Pandas.
• In-depth knowledge of machine learning algorithms, deep learning, and statistical analysis as applied to healthcare data.
• Familiarity with healthcare data standards (e.g., HL7) and privacy regulations (e.g., HIPAA) is preferable
• Experience with electronic health records (EHR), medical imaging data, and healthcare terminologies (e.g., SNOMED, LOINC) is preferable
• Knowledge of cloud computing platforms (e.g., AWS, Azure) and containerization (e.g., Docker) is an advantage.
• Problem-solving skills and the ability to collaborate effectively
• A strong commitment to continuous learning and staying updated with healthcare and machine learning trends.