Note: The job is a remote job and is open to candidates in USA. Molina Healthcare is seeking a Data Scientist to support healthcare-focused data science and artificial intelligence initiatives. The role analyzes and prepares complex datasets, develops and deploys machine learning models, implements agentic workflows and retrieval-augmented generation techniques, and communicates results to technical and non-technical stakeholders.
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
- Collaboration: Work closely with cross-functional teams, including software engineers, product managers, and business analysts, to integrate AI solutions into existing systems and processes
- Research and Development: Stay current with the latest advancements in AI and machine learning and apply these insights to improve existing models and develop new methodologies
- Documentation and Reporting: Create comprehensive documentation of models, methodologies, and results; communicate findings clearly to non-technical stakeholders
Skills
- Bachelor's degree in Computer Science, Data Science, Statistics, or a related field
- 3+ years' work experience as a data scientist preferably in healthcare environment but candidates with suitable experience in other industries will be considered
- Knowledge of big data technologies (e.g., Hadoop, Spark
- 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
- Model Fine-Tuning Expertise: Proven experience in fine-tuning models for specific tasks, ensuring they meet the required performance metrics
- Data Visualization: Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively
- Database Management: Experience with SQL and NoSQL databases, data warehousing, and ETL processes
- Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on developing innovative solutions to complex challenges
- Master's degree in computer science, Data Science, Statistics, or a related field
- Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio etc.) for working with AI workflows and deploying models
- Familiarity with natural language processing (NLP) and computer vision techniques
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