Molina Healthcare is looking to improve models, clean and validate data for uniformity and accuracy, and develop advanced machine learning models and AI solutions to enhance products and services across various healthcare domains.
Requirements
- Knowledge of big data technologies (e.g., Hadoop, Spark)
- Familiar with relational database concepts, and SDLC concepts
- Technical Proficiency: Strong programming skills in languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.
- Statistical Analysis: Excellent understanding of statistical methods and machine learning algorithms, including k-NN, Naive Bayes, SVM, and neural networks.
- Experience with Agentic Workflows: Familiarity with designing and implementing agentic workflows that leverage AI agents for autonomous operations.
- RAG Techniques: Knowledge of retrieval-augmented generation techniques and their application in enhancing AI model outputs.
- Database Management: Experience with SQL and NoSQL databases, data warehousing, and ETL processes.
Responsibilities
- Data Analysis and Interpretation: Extract meaningful insights from complex datasets, identify patterns, and interpret data to inform strategic decision-making.
- Machine Learning Model Development: Design, develop, and train machine learning models using a variety of algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- Agentic Workflows Implementation: Develop and implement agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities.
- RAG Pattern Utilization: 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.
- Model Fine-Tuning: Fine-tune pre-trained models to adapt them to specific tasks or datasets, ensuring optimal performance and relevance in various applications.
- Data Cleaning and Preprocessing: Prepare data for analysis by performing data cleaning, handling missing values, and removing outliers to ensure high-quality inputs for modeling.
- AI Model Deployment and Monitoring: Deploy AI models into production environments, monitor their performance, and adjust as necessary to maintain accuracy and effectiveness.
Other
- Master’s Degree in Computer Science, Data Science, Statistics, or a related field
- 6+ years’ work experience as a data scientist preferably in healthcare environment but candidates with suitable experience in other industries will be considered
- 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.
- PHD or additional experience (Preferred)
