PJCorp2 is looking to revolutionize healthcare operations and enhance member experience by pioneering generative AI healthcare solutions. This involves developing and implementing advanced AI models, optimizing data-driven decision-making, and ensuring ethical data use within the organization.
Requirements
- Strong programming skills in languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.
- Excellent understanding of statistical methods and machine learning algorithms, including k-NN, Naive Bayes, SVM, and neural networks.
- Familiarity with designing and implementing agentic workflows that leverage AI agents for autonomous operations.
- Knowledge of retrieval-augmented generation techniques and their application in enhancing AI model outputs.
- Proven experience in fine-tuning models for specific tasks, ensuring they meet the required performance metrics.
- Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively.
- Experience with SQL and NoSQL databases, data warehousing, and ETL processes.
Responsibilities
- Deploy AI models into production environments, monitor their performance, and adjust as necessary to maintain accuracy and effectiveness and meet all governance and regulatory requirements.
- Design, develop, and train machine learning models using a variety of algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- Develop and implement agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities.
- Employ retrieval-augmented generation patterns to improve the performance of language models, ensuring they can access and utilize external knowledge effectively to enhance their outputs.
- Fine-tune pre-trained models to adapt them to specific tasks or datasets, ensuring optimal performance and relevance in various applications.
- Prepare data for analysis by performing data cleaning, handling missing values, and removing outliers to ensure high-quality inputs for modeling.
- Work closely with cross-functional teams, including software engineers, product managers, and business analysts, to integrate AI solutions into existing systems and processes.
Other
- Responsible for overseeing data science projects, managing and mentoring a team, and aligning data initiatives with business goals.
- Communicate complex technical concepts to non-technical stakeholders.
- Lead initiatives on model governance and model ops to align with regulatory and security requirements.
- Demonstrate critical thinking and the ability to bring order to unstructured problems.
- Strong analytical and problem-solving abilities, with a focus on developing innovative solutions to complex challenges.
